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Family Type and Investment in Education
Family Type and Investment in Education: A Comparison of Genetic and Stepparent Families Keith Zvoch Educational Psychology Program, University of New Mexico, Albuquerque, New Mexico
Data from the U.S. National Education Longitudinal Survey were examined to investigate postsecondary educational investment in two-parent families. Consistent with hypotheses derived from the logic of inclusive fitness theory, contrasting children with two genetic parents with children from stepparent households on a multivariate composite of investment indicators revealed that stepchildren receive significantly less parental support for pursuit of higher education. Univariate tests on the three measures comprising the multivariate composite indicated that relative to children with two genetic parents, stepchildren have parents who (1) delay the start of savings accounts for postsecondary education, (2) put aside less money for subsidizing the costs of higher education, and (3) expect to allocate fewer economic resources to support the first year of postsecondary schooling. Statistical control of child ability, resource availability, and number of family members sharing in parental resources was accomplished in a second multivariate analysis by using child achievement, familial socioeconomic status, and number of financial dependents in each family as covariates. Statistically equating genetic and stepparent families on these measures reduced, but did not eliminate, the investment differences. © 1999 Elsevier Science Inc. KEY WORDS: Parental investment; Stepparents; Discriminative parental solicitude; Postsecondary education; Multivariate analysis of covariance.
W
ithin the past 20 years, investigators throughout the social sciences have devoted increased attention to the study of stepfamilies. Using various methodological frameworks and data derived from both representative and nonrepresentative samples, research conducted in several disciplines has contributed to a growing literature that seeks to understand the complexities of and outcomes associated with stepparent households (see Booth Received February 2, 1999; revised July 30, 1999. Address reprint requests and correspondence to: Keith Zvoch, Educational Psychology Program, Simpson Hall, University of New Mexico, Albuquerque, NM 87131, U.S.A. E-mail: [email protected] Evolution and Human Behavior 20: 453–464 (1999) 1999 Elsevier Science Inc. All rights reserved. 655 Avenue of the Americas, New York, NY 10010
1090-5138/99/$–see front matter PII S1090-5138(99)00024-0
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and Dunn 1994; Cherlin and Furstenberg 1994; Coleman and Ganong 1990; Ihinger-Tallman and Pasley 1997, for reviews). Close investigation of this increasingly common family type (Glick 1989) has uncovered that members of stepfamily households experience higher rates of interpersonal conflict than individuals in comparable genetic parent families. Elevated levels of discord are found in spousal relations (Daly and Wilson 1996), sibling interaction (Anderson and Rice 1992; Hetherington 1993), and stepparent-stepchild associations (Ferri 1984; Flinn 1988, Hetherington and Clingempeel 1992). Further, outcome assessment finds higher divorce rates in remarriages (Becker et al. 1977; Popenoe 1994; White and Booth 1985), less contact between siblings from stepfamilies in adulthood (White and Reidmann 1992), and earlier dispersal of children from stepparent households (Aquilino 1991; Goldscheider and Goldscheider 1993; Kiernan 1992). Inclusive fitness theory (Hamilton 1964), which recognizes both the direct and indirect manner in which individuals contribute genetically to future generations (i.e., through personal and kin-based reproduction), provides a theoretical basis for understanding the heightened conflict and instability observed in stepfamilies. This theory predicts that due to the potential for genetic proliferation through close relatives, individuals will preferentially value and assist those with whom they share common descent. With this broadened understanding of the path(s) to Darwinian fitness, stepfamily dysfunction is thought to stem from a reduction in the shared interests of genetically dissimilar family members (Daly and Wilson 1988a, 1995; Emlen 1995, 1997; Flinn 1988). In intact households, where cooperation among genetically related individuals serves to enhance the inclusive fitness of each family member, a commonality of interest exists (Daly et al. 1997). In these familial situations, individuals are likely to experience and act on the emotional reward that selection has provided for those who make personal sacrifice on behalf of close kin. However, when the structure of a preexisting family is altered by the introduction of genetically unrelated individuals, the psychological benefit associated with within family cooperation correspondingly diminishes. In particular, because a stepparent does not receive the same emotional benefit gained by genetic parents cooperatively investing in a jointly produced offspring, the replacement parent is expected to be less inclined to agree with the family’s genetic parent about the amount and type of investment that is distributed to offspring from previous mateships (Emlen 1997). Given this source of conflict, stepchildren are predicted to secure fewer parental resources and face a greater risk of parental divestment than children with two genetic parents. Several investigations with diverse study populations and various indicators of interpersonal investment (Astone and McLanahan 1991; Downey 1995; Flinn 1988) and extreme divestment (Daly and Wilson 1988b; Hill and Kaplan 1988) support this contention. Following the logic of inclusive fitness theory, the present study utilizes data collected from parents of a nationally representative sample of U.S. high school students to assess postsecondary educational investment in two-parent families. Reasoning that parents of jointly produced offspring will be in greater agreement over allocation of parental resources than parents of offspring produced from one (or both) partner’s prior mateships, it is hypothesized that children with two genetic
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parents will receive more parental support for pursuit of higher education compared to children residing in stepparent households. To minimize potential biases arising from comparison of intact groups, control for between-family type inequity in child ability, resource availability, and number of individuals receiving financial support will be accomplished by statistically equating genetic and stepparent families on measures representing these potential confounds.
METHODS Data Set To explore postsecondary educational investment in two-parent families, data from the U.S. National Education Longitudinal Survey of 1988 (NELS:88) were analyzed. This data set consists of a nationally representative sample of eighth grade students who were surveyed, tested, and then followed-up in a similar manner at 2-year intervals.1 Supplemental background information was provided by the students’ parents, teachers, and school administrators. Participants were selected for inclusion in the survey through a complex sampling process. A two-stage stratified, clustered probability sample design was used to first randomly sample slightly over 1,000 of the approximately 40,000 schools in the U.S.A. that provided instruction to eighth grade students in 1988. From the sampled schools, approximately 24 students were randomly selected from each eighth grade roster. To allow for comparisons across underrepresented subgroups, Asian, Hispanic, and private school students were oversampled. With a weighted adjustment, the 24,599 students in the base year file represent the population of 3,000,000 children who were in the eighth grade in the U.S.A. in 1988. For follow-up data collection, the original student sample was subsampled and then freshened with students who were unavailable to participate in the spring of 1988 to enable analysis of nationally representative tenth and twelfth grade cohorts (NCES 1994a). In the analyses that follow, data from parents and students of the twelth grade cohort were chosen for analysis (N 5 14,039). Survey responses thus reflect parental behavior and child achievement at a point in time toward the end of the child’s secondary educational career.
Participants Collection of student data occurred primarily at the child’s school. Sampled students completed a contextual survey and took a standardized achievement test in a classroom setting. Parent questionnaires were mailed to the home of the surveyed student. Instructions for completing the parent survey stipulated that only the parent with the most knowledge of the child’s current situation should respond (NCES 1 NELS:88 student participants were surveyed and tested when they were in the eighth, tenth, and twelfth grades. For the third follow-up conducted in 1994, when most student participants were 2 years beyond high school graduation, survey information was collected through phone interviews. Cognitive tests were not given to third follow-up participants. A fourth follow-up phone survey is scheduled for the year 2000.
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1994b). Under this condition, the child’s genetic mother responded 78.4% (N 5 11,003) of the time and the child’s genetic father accounted for an additional 16.5% (N 5 2,312) of the responses. Together, stepmothers (N 5 136 [1.0%]) and stepfathers (N 5 81 [0.6%]) provided another 1.6% of the data. The remaining 3.5% of responses were either not identified, missing, or came from another source such as a grandparent or some other adult relative or guardian. Because only one parent filled out the survey, the parental responses potentially contain biases associated with the selfselection process. This bias may be especially problematic when analyzing responses from stepparent families. Because only a small relative number of stepparents actually completed the questionnaire, sample size restrictions do not allow for examining distinctions between stepfamilies in which the child’s genetic parent or the stepparent completed the survey. This limitation will be addressed in the discussion.
Sample Analyzed To select the desired cases for analysis, several identification and nonparticipation data flags were used to include only those students and parents for whom relevant data were available. Consequently, it was first necessary to exclude students who were not part of the twelfth grade cohort or for whom standardized test data were not available. Second, even though 93.2% of parents completed a second follow-up questionnaire, an additional flag was utilized to retain only those students for whom parent data also were available. Third, students living with a single parent or those residing in alternative family situations were removed from the working data file. Fourth, if a parent indicated that their high school senior was not planning to continue his or her education after completion of secondary schooling, these students were excluded from the analysis. A statistically greater number of stepchildren were lost from the analysis as a result of this requirement [x2 (1) 5 26.50, p , .0005]; 8% of stepchildren as opposed to 4% of children from genetic parent families were not planning to continue their education after high school. Fifth, a listwise deletion of missing data removed cases with incomplete data on any of the variables to be analyzed. After these exclusions, 7,161 students remained in the sample. Of these, 6,389 (89.2%) lived in a two genetic parent family and 772 (10.8%) lived in a stepparent family at the time of the data collection.
Measures Parental support for postsecondary education was assessed by analyzing responses to three investment-related questions available in the parent survey. The first of these, an indicator of parental financial preparation, asked, “What grade was your teenager in when you began preparing financially for his/her education after high school?” Respondents could choose from a five-point scale ranging from before first grade to have not begun. To be directionally consistent with the other educational investment indicators, this variable was recoded. Larger values indicate an earlier start to financial preparation for postsecondary education.
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Second, parents were asked, “About how much money have you set aside for your teenager’s future educational needs?” In this case, respondents could chose from one of seven intervals ranging from none to more than $30,000. Respondents who did not answer this question, but earlier indicated that they had not started saving for their child’s education at the time of data collection (i.e., response “have not begun” for the financial preparation variable), were coded as having no educational savings. Third, the parental participant responded to a query of “How much money do you expect to spend on your teenager’s educational expenses next year?” This variable was originally coded on an eight-point scale with one category designated as “my teenager wants to pay for his/her education without our help.” Respondents who chose this option were recoded and included with parents who did not expect to spend anything on their child’s education during the next year. With this adjustment, a seven-point scale was used to measure expected investment, but in this instance, scale intervals ranged from none to more than $20,000. Table 1 presents complete scaling information on each of these variables along with a breakdown of the percentage of participants within family type and three socioeconomic status (SES) levels who selected one of the specified response intervals. Table 1. Percentages of Two-Parent Families with a High School Senior Planning to Continue His/Her Education after Graduation who Reported Various Levels of Investment in That Child’s Impending Postsecondary Education, in Relation to Family Type (Two-Genetic Parents vs. Genetic 1 Stepparent) and Socioeconomic Status High SES Variable Financial preparation Have not begun 10th, 11th, or 12th 7th, 8th, or 9th Between 1st and 6th Before 1st grade Educational savings ($) None ,1,000 1,000 to 5,000 5,001 to 10,000 10,001 to 15,000 15,001 to 30,000 .30,000 Expected investment ($) None ,2,500 2,500 to 4,999 5,000 to 9,999 10,000 to 14,999 15,000 to 19,999 .20,000 N
Mid SES
Low SES
Genetic
Step
Genetic
Step
Genetic
Step
10.6 26.0 20.5 27.2 20.7
16.9 27.2 29.2 16.0 10.0
25.1 31.1 18.9 13.7 11.3
34.8 35.3 14.5 7.9 7.4
50.5 28.3 12.2 5.7 3.5
53.2 31.3 8.3 3.3 3.9
14.5 5.8 21.5 17.5 12.7 14.7 13.2
20.4 6.8 32.1 16.9 7.3 10.6 5.9
30.7 14.2 30.8 11.8 6.2 4.2 2.1
40.0 13.0 29.1 10.9 3.7 2.2 1.1
62.0 13.0 16.5 5.3 1.9 1.1 .3
63.5 7.8 25.4 1.2 .8 0 1.3
4.4 14.7 22.4 26.1 15.4 8.0 9.0 2662
13.7 24.7 22.9 21.1 8.8 5.1 3.6 232
18.7 29.0 25.9 18.7 5.0 1.5 1.3 2966
32.0 33.7 19.4 10.2 3.2 .8 .8 436
39.2 29.0 16.4 10.6 3.9 .4 .5 761
37.3 28.4 22.7 8.8 2.3 .5 0 104
Note. The quartile distribution of socioeconomic status (SES) (i.e., variable F2SES3Q in the NELS:88 data set) was recoded to collapse the second and third quartile to identify the top 25%, the middle 50%, and the bottom 25% of respondents who remained in the sample. These percentages are weighted estimates.
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In the second analysis, measures of child achievement, familial SES, and number of financial dependents in each family were used as a set of covariates. Child achievement was constructed from standardized test data; familial SES and number of financial dependents were taken directly from the set of variables available in the NELS:88 data base. Principal components analysis (PCA) was used to form an aggregate child achievement score. Using standardized test data from four subject areas (i.e., reading, science, math, social studies), a PCA extracted one component with an eigenvalue .1. This component captured 80% of the variance of the original variables. All original variables had large commonalities and were strongly correlated with the extracted component (i.e., correlations ranged from .88 to .90). Computed component scores served as the achievement covariate. The second variable used as a covariate, a standardized composite indicating the socioeconomic background of each family in the dataset, was compiled by National Center for Education Statistics (NCES) staff from parent (and/or student questionnaire) items seeking information on parental education level, occupation, and yearly family income (see NCES 1994b: J11–J13, for details on the composition of this variable). Finally, the third covariate, number of family members receiving financial support, was derived from parental response to a survey item asking, “Altogether, how many people are financially dependent upon you (or you and your spouse/partner)? Count everyone who receives one-half or more of their financial support from you or your spouse/partner. Include individuals not living with you and your spouse/partner, but do not include yourself or your spouse/partner.” Respondents could choose from a scale ranging from none to eight or more.
RESULTS To begin, a one-way multivariate analysis of variance (MANOVA) was performed on the three investment-related dependent variables. Family type served as the grouping factor. Statistical model assumptions underlying the use of MANOVA were met. Departures from multivariate normality were minimal, determinants of the covariance matrices were proportional to group size,2 and no obvious dependencies among residuals were found. Examination of within-cell scatterplots revealed the existence of linear relationships among all pairs of dependent variables. A within-cell search for univariate and multivariate outliers identified a few cases with an unusual combination of values, but when models were run with and without these cases, results were not significantly affected. All valid cases were included in the following analyses. Using Wilks’ test of multivariate significance, family type was significantly related to the weighted multivariate combination of educational investment measures 2 The homogeneity of covariance matrices assumption was violated based on the results of Box’s test [Box’s M 5 33.19, F (6,1053750) 5 5.51, p , .0005]. However, because the generalized variance associated with genetic parent families (n 5 1,696, | Sgen | 5 6.13) was larger than the generalized variance associated with stepparent families (n 5 247, | Sstep | 5 2.42), multivariate tests of significance actually become more conservative (Stevens 1992).
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[L 5 .976, F (3, 1939) 5 15.63, p , .0005, h2 5 .024]. Examination of the standardized discriminant function coefficients (SDFC) used to weight the multivariate composite revealed that expected investment in postsecondary education during the following year (SDFC 5 .775), and grade in which financial preparation began (SDFC 5 .525) were most important in forming the function that discriminated the two family types. Educational savings contributed less to the function (SDFC 5 2.080). Inspection of the structure coefficients indicated that the observed measures had moderate to strong correlations with the multivariate composite, expected investment (r 5 .89), financial preparation (r 5 .69), and educational savings (r 5 .66). Univariate ANOVAs on each of the three measures comprising the multivariate composite revealed statistically significant mean investment differences between family type. Genetic parent families started saving for postsecondary education earlier than stepparent families [F (1, 1941) 5 22.60, MSE 5 1.78, p , .05, d 5 .38]; genetic parent families put aside more money for supporting higher education relative to stepparent families [F (1, 1941) 5 20.29, MSE 5 3.26, p , .05, d 5 .43]; and genetic parent families expected to spend more to support the first year of postsecondary schooling relative to stepparent families [F (1, 1941) 5 36.96, MSE 5 2.35, p, .05, d 5 .53]. Alpha was adjusted for multiple testing (i.e., .05/3 5 .017) to maintain the probability of type I error at .05. After establishing statistically significant differences between the family types, a second multivariate analysis was conducted to determine if the observed mean investment disparities could be explained by resource- and/or child-related factors. Using an aggregate child achievement score, familial SES, and the number of financial dependents in each family as covariates, a multivariate analysis of covariance (MANCOVA) was performed. Model assumptions underlying the proper use of MANCOVA were met. A significant linear relationship between the set of covariates and the set of dependent variables was found [L 5 .679, F (9, 4712) 5 90.35, p , .0005, h2 5 .321] and the assumption of homogeneity of regression hyperplanes was satisfied [L 5 .996, F (9, 4705) 5 .896, p 5 .528], enabling valid interpretation of the covariance analysis. Using Wilks’ test of multivariate significance, family type remained significantly related to the weighted combination of investment indicators [L 5 .984, F (3, 1936) 5 10.57, p , .0005, h2 5 .016]. Function and structure coefficients were not meaningfully influenced (i.e., the magnitude and rank ordering of the coefficients did not change by including covariates in the model). Univariate tests on the adjusted means revealed statistically significant investment contrasts on all three dependent measures. Controlling for resource availability, child achievement, and number of financial dependents, genetic parent families began financial preparations for postsecondary schooling earlier than stepparent families [F (1, 1938) 5 13.53, MSE 5 1.57, p , .05, d 5 .28], genetic parent families put aside more money for supporting higher education relative to stepparent families [F (1, 1938) 5 9.71, MSE 5 2.48, p , .05, d 5 .26], and genetic parent families expected to spend more to support the first year of postsecondary education relative to stepparent families [F (1, 1938) 5 22.63, MSE 5 1.81, p , .05, d 5 36]. Statistical significance was again assessed at .05/3 5 .017. Table 2 presents ob-
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Table 2.
Genetic and Stepparent Family Observed and Adjusted Univariate Means Genetic
Variable Fin prep Ed savings Exp invest
Observed
Adjusted
2.70 3.10 3.11
2.64 2.99 3.01
Step SE
95% CI
.033 .045 .038
2.57, 2.76 2.90, 3.07 2.94, 3.08
Observed
Adjusted
2.26 2.54 2.48
2.32 2.65 2.57
SE
95% CI
.078 .100 .170
2.17, 2.47 2.45, 2.85 2.40, 2.74
Note. Confidence intervals were calculated using the effective sample size for each family type (genetic, n 5 1, 696; step, n 5 247). Fin prep 5 financial preparation; ED savings 5 educational savings; Exp invest 5 expected investment; variables F2P80, F2P81, and F2P90 in the NELS:88 data set, respectively.
served and adjusted means for each dependent measure, along with 95% confidence intervals for estimating adjusted population mean values.3
DISCUSSION Provisioning offspring is both a costly and a beneficial endeavor for parents. Costs are incurred through the expenditure of limited energetic resources and lost reproductive potential. Benefits are gained in terms of the positive impact parental resource distribution has on offspring fitness (Clutton-Brock 1991). In Homo sapiens, partially owing to the prolonged period of juvenile dependency and the large amount of extrasomatic investment necessary to produce competitive offspring (Kaplan 1996; Lancaster 1997), evolutionary theorists have argued that selection should have favored a parental psychology that, all things being equal, promotes investment in offspring likely to contribute to parental fitness (Alexander 1979; Daly and Wilson 1980, 1988a, 1995). In this article, parental support for a child’s postsecondary education served as the basis for investigating whether children genetically unrelated to one of their parents find themselves subject to tactics of parental discrimination. Inferring a lack of parental consensus on the amount of resources needed to finance a stepchild’s education, it was hypothesized that, in comparison with families containing parents jointly benefited by expenditures on offspring, stepparent families would offer fewer parental resources in support of children produced from previous mateships. To allow for a minimally biased test of the hypothesis, genetic and stepparent families were statistically equated on several theoretically important variables (i.e., familial economic and educational resource availability, child ability, and number of financial dependents). Controlling for these potential confounds, multivariate and univariate tests of statistical significance indicated
3
All statistics presented in this article are weighted estimates. The second follow-up parent weight (F2PAQWT) was applied in all calculations to adjust for unit nonresponse and the oversampling of certain subgroups. Statistical tests of significance were conducted after adjusting for the survey’s design effect (DEFF 5 3.69). Using the formula [(1/DEFF) * (F2PAQWT/mean of F2PAQWT)], a new sample weight was created to enable unbiased significance testing. Use of the new sample weight reduced the effective sample size of genetic parent families to 1,696 and stepparent families to 247. Further information on sample weights and design effects can be found in NCES (1994b).
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that stepchildren were likely to receive less parental support for pursuit of higher education when considered relative to children from two genetic parent households. Although it is unlikely that differences in the level of postsecondary educational support provided by genetic and stepparent families were attributable to sampling error, the question remains as to whether they have any practical import. Calculation of strength of association measures revealed a relatively small amount of variation in the multivariate educational investment composite accounted for by family type (2%), and univariate effect size estimates also were generally small (d values ranged from .26 to .36). Contextually, in terms of the dependent measures’ original scale units and with adjustment for covariates, stepchildren have parents who start savings accounts approximately 1 year later, save approximately $1600 less for subsidizing the costs of higher education, and expect to spend approximately $1400 less to support the first year of postsecondary schooling, relative to children with two genetic parents.4 Based on these findings, between-family type investment disparities do not appear practically substantive. On average, stepchildren bound for postsecondary education were likely to receive a nontrival amount of parental support for pursuit of this endeavor, even though it was somewhat less than the amount received by genetic children. Educational opportunity thus is unlikely to have been severely compromised for stepchildren with postsecondary educational aspirations.5 Consideration of several methodological caveats may assist in explaining the muted influence of family type in this study. First, continuation of education often is contingent on first attaining a secondary degree. Comparison of children living in a stepfamily at the time of base year data collection with children living in a two genetic parent household revealed that significantly more stepchildren dropped out of school between eighth and twelth grade [x2 (1) 5 123.39, p , .0005]; 17% of stepchildren as opposed to 8% of genetic children did not complete high school. Second, given that a child was still in school toward the end of twelth grade, only children who were planning to continue their education after high school were included in the analyses. With twice as many stepchildren not planning to pursue a postsecondary education (i.e., 8% of stepchildren vs. 4% present of genetic children), the total extent of parental bias against stepchildren may not have been captured with the measures used in this study. Third, through self-selection into the study, it is possible that the parental responses were confounded by the bias toward questionnaire completion by genetic parents [i.e., only 75 (10%) of the final 772 stepfamily respondents were actually stepparents]. Because only a small number of stepparents 4 These estimates are rough approximations. Due to the presence of open-ended categories, a decision was made to constrain the size of the open-ended intervals using the range of each variable’s preceding closed interval (e.g., the final category for educational savings was constrained to range from 30,001 to 45,000). The midpoint of each interval (in dollars for educational savings and expected investment; in years for financial preparation) was calculated to serve as the basis for rescaling the dependent variables. Using each variable’s new scale as input, the MANCOVA was rerun. Between-family type investment disparities were derived from the difference in each group’s mean investment on each of the dependent measures. 5 As alluded to in the next paragraph, the measures utilized in this study may not have tapped the extent to which postsecondary education actually is available to stepchildren. Because significantly more stepchildren drop out of high school and because significantly more stepchildren do not plan to continue their education after secondary schooling, the results of this study likely underestimate a stepchild’s actual opportunity for an attempt at attaining a postsecondary degree.
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completed the parent questionnaire, it is open to speculation whether the genetic parent responses in these families are reflective of stepparent intentions. Additional analyses (not presented) utilizing the small number of stepparents who did respond to the questionnaire revealed that stepparents reported lower mean levels of support on each educational investment indicator when considered relative to responses provided by stepfamily genetic parent participants. These within-family type reporting discrepancies were not statistically significant, but potentially imply that the effect of stepparent influence may be underestimated in the analyses presented.
CONCLUSION The present study provides some support for expectations derived from application of evolutionary logic. With control of several potential confounds, stepchildren were likely to receive less parental support for pursuit of postsecondary education, relative to children with two genetic parents. However, possibly due to sample exclusions, unmeasured displays of mating effort, and/or other limitations in the data source, these between-family type investment disparities were not large in magnitude. Nonetheless, because statistically significant between-family type investment differences still remain after the conservative analytic approach taken in this research, a concern is raised. By utilizing data derived from self-selected parental participants and by focusing the analysis only on children who received enough parental support to remain in school and have postsecondary educational aspirations, this study, although demonstrating nonchance between family-type investment disparities, is likely to have underestimated stepchildren’s relative disadvantage in gaining access to higher levels of education. Future investigation, with comprehensive, objective, and psychometrically sound measures, will be necessary to determine the true extent to which stepchildren face subtle and overt tactics of parental discrimination. This research was supported by a grant from the American Educational Research Association, which receives funds for its “AERA Grants Program” from the National Center for Education Statistics and the Office of Educational Research and Improvement (U.S. Department of Education) and the National Science Foundation under NSF Grant #RED-9452861. Opinions reflect those of the author and do not necessarily reflect those of the granting agencies. I would like to thank Martin Daly, Steven Gangestad, Candace Schau, Joseph Stevens, Margo Wilson, and two anonymous reviewers for helpful comments on earlier drafts of this paper. Any remaining conceptual, computational, or interpretational inaccuracies are solely the author’s responsibility.
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NCES (National Center for Education Statistics). National Education Longitudinal Survey of 1988: Second Follow-Up Parent Component Data File User’s Manual, 94-378. Washington: U.S. Department of Education, 1994b. Popenoe, D. The evolution of marriage and the problem of stepfamilies: a biosocial perspective. In Stepfamilies: Who Benefits? Who Does Not?, A. Booth and J. Dunn (Eds.). Hillsdale: Erlbaum, 1994, pp. 3–28. Stevens, J. Applied Multivariate Statistics for the Social Sciences. 2nd ed. Hillsdale: Erlbaum, 1992. White, L.K., and Booth, A. The quality and stability of remarriages: the role of stepchildren. American Sociological Review 50:689–698, 1985. White, L.K., and Reidmann, A.C. When the Brady Bunch grows up: relations between fullsiblings and stepsiblings in adulthood. Journal of Marriage and the Family 54:197–208, 1992.
Data from the U.S. National Education Longitudinal Survey were examined to investigate postsecondary educational investment in two-parent families. Consistent with hypotheses derived from the logic of inclusive fitness theory, contrasting children with two genetic parents with children from stepparent households on a multivariate composite of investment indicators revealed that stepchildren receive significantly less parental support for pursuit of higher education. Univariate tests on the three measures comprising the multivariate composite indicated that relative to children with two genetic parents, stepchildren have parents who (1) delay the start of savings accounts for postsecondary education, (2) put aside less money for subsidizing the costs of higher education, and (3) expect to allocate fewer economic resources to support the first year of postsecondary schooling. Statistical control of child ability, resource availability, and number of family members sharing in parental resources was accomplished in a second multivariate analysis by using child achievement, familial socioeconomic status, and number of financial dependents in each family as covariates. Statistically equating genetic and stepparent families on these measures reduced, but did not eliminate, the investment differences. © 1999 Elsevier Science Inc. KEY WORDS: Parental investment; Stepparents; Discriminative parental solicitude; Postsecondary education; Multivariate analysis of covariance.
W
ithin the past 20 years, investigators throughout the social sciences have devoted increased attention to the study of stepfamilies. Using various methodological frameworks and data derived from both representative and nonrepresentative samples, research conducted in several disciplines has contributed to a growing literature that seeks to understand the complexities of and outcomes associated with stepparent households (see Booth Received February 2, 1999; revised July 30, 1999. Address reprint requests and correspondence to: Keith Zvoch, Educational Psychology Program, Simpson Hall, University of New Mexico, Albuquerque, NM 87131, U.S.A. E-mail: [email protected] Evolution and Human Behavior 20: 453–464 (1999) 1999 Elsevier Science Inc. All rights reserved. 655 Avenue of the Americas, New York, NY 10010
1090-5138/99/$–see front matter PII S1090-5138(99)00024-0
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and Dunn 1994; Cherlin and Furstenberg 1994; Coleman and Ganong 1990; Ihinger-Tallman and Pasley 1997, for reviews). Close investigation of this increasingly common family type (Glick 1989) has uncovered that members of stepfamily households experience higher rates of interpersonal conflict than individuals in comparable genetic parent families. Elevated levels of discord are found in spousal relations (Daly and Wilson 1996), sibling interaction (Anderson and Rice 1992; Hetherington 1993), and stepparent-stepchild associations (Ferri 1984; Flinn 1988, Hetherington and Clingempeel 1992). Further, outcome assessment finds higher divorce rates in remarriages (Becker et al. 1977; Popenoe 1994; White and Booth 1985), less contact between siblings from stepfamilies in adulthood (White and Reidmann 1992), and earlier dispersal of children from stepparent households (Aquilino 1991; Goldscheider and Goldscheider 1993; Kiernan 1992). Inclusive fitness theory (Hamilton 1964), which recognizes both the direct and indirect manner in which individuals contribute genetically to future generations (i.e., through personal and kin-based reproduction), provides a theoretical basis for understanding the heightened conflict and instability observed in stepfamilies. This theory predicts that due to the potential for genetic proliferation through close relatives, individuals will preferentially value and assist those with whom they share common descent. With this broadened understanding of the path(s) to Darwinian fitness, stepfamily dysfunction is thought to stem from a reduction in the shared interests of genetically dissimilar family members (Daly and Wilson 1988a, 1995; Emlen 1995, 1997; Flinn 1988). In intact households, where cooperation among genetically related individuals serves to enhance the inclusive fitness of each family member, a commonality of interest exists (Daly et al. 1997). In these familial situations, individuals are likely to experience and act on the emotional reward that selection has provided for those who make personal sacrifice on behalf of close kin. However, when the structure of a preexisting family is altered by the introduction of genetically unrelated individuals, the psychological benefit associated with within family cooperation correspondingly diminishes. In particular, because a stepparent does not receive the same emotional benefit gained by genetic parents cooperatively investing in a jointly produced offspring, the replacement parent is expected to be less inclined to agree with the family’s genetic parent about the amount and type of investment that is distributed to offspring from previous mateships (Emlen 1997). Given this source of conflict, stepchildren are predicted to secure fewer parental resources and face a greater risk of parental divestment than children with two genetic parents. Several investigations with diverse study populations and various indicators of interpersonal investment (Astone and McLanahan 1991; Downey 1995; Flinn 1988) and extreme divestment (Daly and Wilson 1988b; Hill and Kaplan 1988) support this contention. Following the logic of inclusive fitness theory, the present study utilizes data collected from parents of a nationally representative sample of U.S. high school students to assess postsecondary educational investment in two-parent families. Reasoning that parents of jointly produced offspring will be in greater agreement over allocation of parental resources than parents of offspring produced from one (or both) partner’s prior mateships, it is hypothesized that children with two genetic
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parents will receive more parental support for pursuit of higher education compared to children residing in stepparent households. To minimize potential biases arising from comparison of intact groups, control for between-family type inequity in child ability, resource availability, and number of individuals receiving financial support will be accomplished by statistically equating genetic and stepparent families on measures representing these potential confounds.
METHODS Data Set To explore postsecondary educational investment in two-parent families, data from the U.S. National Education Longitudinal Survey of 1988 (NELS:88) were analyzed. This data set consists of a nationally representative sample of eighth grade students who were surveyed, tested, and then followed-up in a similar manner at 2-year intervals.1 Supplemental background information was provided by the students’ parents, teachers, and school administrators. Participants were selected for inclusion in the survey through a complex sampling process. A two-stage stratified, clustered probability sample design was used to first randomly sample slightly over 1,000 of the approximately 40,000 schools in the U.S.A. that provided instruction to eighth grade students in 1988. From the sampled schools, approximately 24 students were randomly selected from each eighth grade roster. To allow for comparisons across underrepresented subgroups, Asian, Hispanic, and private school students were oversampled. With a weighted adjustment, the 24,599 students in the base year file represent the population of 3,000,000 children who were in the eighth grade in the U.S.A. in 1988. For follow-up data collection, the original student sample was subsampled and then freshened with students who were unavailable to participate in the spring of 1988 to enable analysis of nationally representative tenth and twelfth grade cohorts (NCES 1994a). In the analyses that follow, data from parents and students of the twelth grade cohort were chosen for analysis (N 5 14,039). Survey responses thus reflect parental behavior and child achievement at a point in time toward the end of the child’s secondary educational career.
Participants Collection of student data occurred primarily at the child’s school. Sampled students completed a contextual survey and took a standardized achievement test in a classroom setting. Parent questionnaires were mailed to the home of the surveyed student. Instructions for completing the parent survey stipulated that only the parent with the most knowledge of the child’s current situation should respond (NCES 1 NELS:88 student participants were surveyed and tested when they were in the eighth, tenth, and twelfth grades. For the third follow-up conducted in 1994, when most student participants were 2 years beyond high school graduation, survey information was collected through phone interviews. Cognitive tests were not given to third follow-up participants. A fourth follow-up phone survey is scheduled for the year 2000.
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1994b). Under this condition, the child’s genetic mother responded 78.4% (N 5 11,003) of the time and the child’s genetic father accounted for an additional 16.5% (N 5 2,312) of the responses. Together, stepmothers (N 5 136 [1.0%]) and stepfathers (N 5 81 [0.6%]) provided another 1.6% of the data. The remaining 3.5% of responses were either not identified, missing, or came from another source such as a grandparent or some other adult relative or guardian. Because only one parent filled out the survey, the parental responses potentially contain biases associated with the selfselection process. This bias may be especially problematic when analyzing responses from stepparent families. Because only a small relative number of stepparents actually completed the questionnaire, sample size restrictions do not allow for examining distinctions between stepfamilies in which the child’s genetic parent or the stepparent completed the survey. This limitation will be addressed in the discussion.
Sample Analyzed To select the desired cases for analysis, several identification and nonparticipation data flags were used to include only those students and parents for whom relevant data were available. Consequently, it was first necessary to exclude students who were not part of the twelfth grade cohort or for whom standardized test data were not available. Second, even though 93.2% of parents completed a second follow-up questionnaire, an additional flag was utilized to retain only those students for whom parent data also were available. Third, students living with a single parent or those residing in alternative family situations were removed from the working data file. Fourth, if a parent indicated that their high school senior was not planning to continue his or her education after completion of secondary schooling, these students were excluded from the analysis. A statistically greater number of stepchildren were lost from the analysis as a result of this requirement [x2 (1) 5 26.50, p , .0005]; 8% of stepchildren as opposed to 4% of children from genetic parent families were not planning to continue their education after high school. Fifth, a listwise deletion of missing data removed cases with incomplete data on any of the variables to be analyzed. After these exclusions, 7,161 students remained in the sample. Of these, 6,389 (89.2%) lived in a two genetic parent family and 772 (10.8%) lived in a stepparent family at the time of the data collection.
Measures Parental support for postsecondary education was assessed by analyzing responses to three investment-related questions available in the parent survey. The first of these, an indicator of parental financial preparation, asked, “What grade was your teenager in when you began preparing financially for his/her education after high school?” Respondents could choose from a five-point scale ranging from before first grade to have not begun. To be directionally consistent with the other educational investment indicators, this variable was recoded. Larger values indicate an earlier start to financial preparation for postsecondary education.
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Second, parents were asked, “About how much money have you set aside for your teenager’s future educational needs?” In this case, respondents could chose from one of seven intervals ranging from none to more than $30,000. Respondents who did not answer this question, but earlier indicated that they had not started saving for their child’s education at the time of data collection (i.e., response “have not begun” for the financial preparation variable), were coded as having no educational savings. Third, the parental participant responded to a query of “How much money do you expect to spend on your teenager’s educational expenses next year?” This variable was originally coded on an eight-point scale with one category designated as “my teenager wants to pay for his/her education without our help.” Respondents who chose this option were recoded and included with parents who did not expect to spend anything on their child’s education during the next year. With this adjustment, a seven-point scale was used to measure expected investment, but in this instance, scale intervals ranged from none to more than $20,000. Table 1 presents complete scaling information on each of these variables along with a breakdown of the percentage of participants within family type and three socioeconomic status (SES) levels who selected one of the specified response intervals. Table 1. Percentages of Two-Parent Families with a High School Senior Planning to Continue His/Her Education after Graduation who Reported Various Levels of Investment in That Child’s Impending Postsecondary Education, in Relation to Family Type (Two-Genetic Parents vs. Genetic 1 Stepparent) and Socioeconomic Status High SES Variable Financial preparation Have not begun 10th, 11th, or 12th 7th, 8th, or 9th Between 1st and 6th Before 1st grade Educational savings ($) None ,1,000 1,000 to 5,000 5,001 to 10,000 10,001 to 15,000 15,001 to 30,000 .30,000 Expected investment ($) None ,2,500 2,500 to 4,999 5,000 to 9,999 10,000 to 14,999 15,000 to 19,999 .20,000 N
Mid SES
Low SES
Genetic
Step
Genetic
Step
Genetic
Step
10.6 26.0 20.5 27.2 20.7
16.9 27.2 29.2 16.0 10.0
25.1 31.1 18.9 13.7 11.3
34.8 35.3 14.5 7.9 7.4
50.5 28.3 12.2 5.7 3.5
53.2 31.3 8.3 3.3 3.9
14.5 5.8 21.5 17.5 12.7 14.7 13.2
20.4 6.8 32.1 16.9 7.3 10.6 5.9
30.7 14.2 30.8 11.8 6.2 4.2 2.1
40.0 13.0 29.1 10.9 3.7 2.2 1.1
62.0 13.0 16.5 5.3 1.9 1.1 .3
63.5 7.8 25.4 1.2 .8 0 1.3
4.4 14.7 22.4 26.1 15.4 8.0 9.0 2662
13.7 24.7 22.9 21.1 8.8 5.1 3.6 232
18.7 29.0 25.9 18.7 5.0 1.5 1.3 2966
32.0 33.7 19.4 10.2 3.2 .8 .8 436
39.2 29.0 16.4 10.6 3.9 .4 .5 761
37.3 28.4 22.7 8.8 2.3 .5 0 104
Note. The quartile distribution of socioeconomic status (SES) (i.e., variable F2SES3Q in the NELS:88 data set) was recoded to collapse the second and third quartile to identify the top 25%, the middle 50%, and the bottom 25% of respondents who remained in the sample. These percentages are weighted estimates.
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In the second analysis, measures of child achievement, familial SES, and number of financial dependents in each family were used as a set of covariates. Child achievement was constructed from standardized test data; familial SES and number of financial dependents were taken directly from the set of variables available in the NELS:88 data base. Principal components analysis (PCA) was used to form an aggregate child achievement score. Using standardized test data from four subject areas (i.e., reading, science, math, social studies), a PCA extracted one component with an eigenvalue .1. This component captured 80% of the variance of the original variables. All original variables had large commonalities and were strongly correlated with the extracted component (i.e., correlations ranged from .88 to .90). Computed component scores served as the achievement covariate. The second variable used as a covariate, a standardized composite indicating the socioeconomic background of each family in the dataset, was compiled by National Center for Education Statistics (NCES) staff from parent (and/or student questionnaire) items seeking information on parental education level, occupation, and yearly family income (see NCES 1994b: J11–J13, for details on the composition of this variable). Finally, the third covariate, number of family members receiving financial support, was derived from parental response to a survey item asking, “Altogether, how many people are financially dependent upon you (or you and your spouse/partner)? Count everyone who receives one-half or more of their financial support from you or your spouse/partner. Include individuals not living with you and your spouse/partner, but do not include yourself or your spouse/partner.” Respondents could choose from a scale ranging from none to eight or more.
RESULTS To begin, a one-way multivariate analysis of variance (MANOVA) was performed on the three investment-related dependent variables. Family type served as the grouping factor. Statistical model assumptions underlying the use of MANOVA were met. Departures from multivariate normality were minimal, determinants of the covariance matrices were proportional to group size,2 and no obvious dependencies among residuals were found. Examination of within-cell scatterplots revealed the existence of linear relationships among all pairs of dependent variables. A within-cell search for univariate and multivariate outliers identified a few cases with an unusual combination of values, but when models were run with and without these cases, results were not significantly affected. All valid cases were included in the following analyses. Using Wilks’ test of multivariate significance, family type was significantly related to the weighted multivariate combination of educational investment measures 2 The homogeneity of covariance matrices assumption was violated based on the results of Box’s test [Box’s M 5 33.19, F (6,1053750) 5 5.51, p , .0005]. However, because the generalized variance associated with genetic parent families (n 5 1,696, | Sgen | 5 6.13) was larger than the generalized variance associated with stepparent families (n 5 247, | Sstep | 5 2.42), multivariate tests of significance actually become more conservative (Stevens 1992).
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[L 5 .976, F (3, 1939) 5 15.63, p , .0005, h2 5 .024]. Examination of the standardized discriminant function coefficients (SDFC) used to weight the multivariate composite revealed that expected investment in postsecondary education during the following year (SDFC 5 .775), and grade in which financial preparation began (SDFC 5 .525) were most important in forming the function that discriminated the two family types. Educational savings contributed less to the function (SDFC 5 2.080). Inspection of the structure coefficients indicated that the observed measures had moderate to strong correlations with the multivariate composite, expected investment (r 5 .89), financial preparation (r 5 .69), and educational savings (r 5 .66). Univariate ANOVAs on each of the three measures comprising the multivariate composite revealed statistically significant mean investment differences between family type. Genetic parent families started saving for postsecondary education earlier than stepparent families [F (1, 1941) 5 22.60, MSE 5 1.78, p , .05, d 5 .38]; genetic parent families put aside more money for supporting higher education relative to stepparent families [F (1, 1941) 5 20.29, MSE 5 3.26, p , .05, d 5 .43]; and genetic parent families expected to spend more to support the first year of postsecondary schooling relative to stepparent families [F (1, 1941) 5 36.96, MSE 5 2.35, p, .05, d 5 .53]. Alpha was adjusted for multiple testing (i.e., .05/3 5 .017) to maintain the probability of type I error at .05. After establishing statistically significant differences between the family types, a second multivariate analysis was conducted to determine if the observed mean investment disparities could be explained by resource- and/or child-related factors. Using an aggregate child achievement score, familial SES, and the number of financial dependents in each family as covariates, a multivariate analysis of covariance (MANCOVA) was performed. Model assumptions underlying the proper use of MANCOVA were met. A significant linear relationship between the set of covariates and the set of dependent variables was found [L 5 .679, F (9, 4712) 5 90.35, p , .0005, h2 5 .321] and the assumption of homogeneity of regression hyperplanes was satisfied [L 5 .996, F (9, 4705) 5 .896, p 5 .528], enabling valid interpretation of the covariance analysis. Using Wilks’ test of multivariate significance, family type remained significantly related to the weighted combination of investment indicators [L 5 .984, F (3, 1936) 5 10.57, p , .0005, h2 5 .016]. Function and structure coefficients were not meaningfully influenced (i.e., the magnitude and rank ordering of the coefficients did not change by including covariates in the model). Univariate tests on the adjusted means revealed statistically significant investment contrasts on all three dependent measures. Controlling for resource availability, child achievement, and number of financial dependents, genetic parent families began financial preparations for postsecondary schooling earlier than stepparent families [F (1, 1938) 5 13.53, MSE 5 1.57, p , .05, d 5 .28], genetic parent families put aside more money for supporting higher education relative to stepparent families [F (1, 1938) 5 9.71, MSE 5 2.48, p , .05, d 5 .26], and genetic parent families expected to spend more to support the first year of postsecondary education relative to stepparent families [F (1, 1938) 5 22.63, MSE 5 1.81, p , .05, d 5 36]. Statistical significance was again assessed at .05/3 5 .017. Table 2 presents ob-
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Table 2.
Genetic and Stepparent Family Observed and Adjusted Univariate Means Genetic
Variable Fin prep Ed savings Exp invest
Observed
Adjusted
2.70 3.10 3.11
2.64 2.99 3.01
Step SE
95% CI
.033 .045 .038
2.57, 2.76 2.90, 3.07 2.94, 3.08
Observed
Adjusted
2.26 2.54 2.48
2.32 2.65 2.57
SE
95% CI
.078 .100 .170
2.17, 2.47 2.45, 2.85 2.40, 2.74
Note. Confidence intervals were calculated using the effective sample size for each family type (genetic, n 5 1, 696; step, n 5 247). Fin prep 5 financial preparation; ED savings 5 educational savings; Exp invest 5 expected investment; variables F2P80, F2P81, and F2P90 in the NELS:88 data set, respectively.
served and adjusted means for each dependent measure, along with 95% confidence intervals for estimating adjusted population mean values.3
DISCUSSION Provisioning offspring is both a costly and a beneficial endeavor for parents. Costs are incurred through the expenditure of limited energetic resources and lost reproductive potential. Benefits are gained in terms of the positive impact parental resource distribution has on offspring fitness (Clutton-Brock 1991). In Homo sapiens, partially owing to the prolonged period of juvenile dependency and the large amount of extrasomatic investment necessary to produce competitive offspring (Kaplan 1996; Lancaster 1997), evolutionary theorists have argued that selection should have favored a parental psychology that, all things being equal, promotes investment in offspring likely to contribute to parental fitness (Alexander 1979; Daly and Wilson 1980, 1988a, 1995). In this article, parental support for a child’s postsecondary education served as the basis for investigating whether children genetically unrelated to one of their parents find themselves subject to tactics of parental discrimination. Inferring a lack of parental consensus on the amount of resources needed to finance a stepchild’s education, it was hypothesized that, in comparison with families containing parents jointly benefited by expenditures on offspring, stepparent families would offer fewer parental resources in support of children produced from previous mateships. To allow for a minimally biased test of the hypothesis, genetic and stepparent families were statistically equated on several theoretically important variables (i.e., familial economic and educational resource availability, child ability, and number of financial dependents). Controlling for these potential confounds, multivariate and univariate tests of statistical significance indicated
3
All statistics presented in this article are weighted estimates. The second follow-up parent weight (F2PAQWT) was applied in all calculations to adjust for unit nonresponse and the oversampling of certain subgroups. Statistical tests of significance were conducted after adjusting for the survey’s design effect (DEFF 5 3.69). Using the formula [(1/DEFF) * (F2PAQWT/mean of F2PAQWT)], a new sample weight was created to enable unbiased significance testing. Use of the new sample weight reduced the effective sample size of genetic parent families to 1,696 and stepparent families to 247. Further information on sample weights and design effects can be found in NCES (1994b).
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that stepchildren were likely to receive less parental support for pursuit of higher education when considered relative to children from two genetic parent households. Although it is unlikely that differences in the level of postsecondary educational support provided by genetic and stepparent families were attributable to sampling error, the question remains as to whether they have any practical import. Calculation of strength of association measures revealed a relatively small amount of variation in the multivariate educational investment composite accounted for by family type (2%), and univariate effect size estimates also were generally small (d values ranged from .26 to .36). Contextually, in terms of the dependent measures’ original scale units and with adjustment for covariates, stepchildren have parents who start savings accounts approximately 1 year later, save approximately $1600 less for subsidizing the costs of higher education, and expect to spend approximately $1400 less to support the first year of postsecondary schooling, relative to children with two genetic parents.4 Based on these findings, between-family type investment disparities do not appear practically substantive. On average, stepchildren bound for postsecondary education were likely to receive a nontrival amount of parental support for pursuit of this endeavor, even though it was somewhat less than the amount received by genetic children. Educational opportunity thus is unlikely to have been severely compromised for stepchildren with postsecondary educational aspirations.5 Consideration of several methodological caveats may assist in explaining the muted influence of family type in this study. First, continuation of education often is contingent on first attaining a secondary degree. Comparison of children living in a stepfamily at the time of base year data collection with children living in a two genetic parent household revealed that significantly more stepchildren dropped out of school between eighth and twelth grade [x2 (1) 5 123.39, p , .0005]; 17% of stepchildren as opposed to 8% of genetic children did not complete high school. Second, given that a child was still in school toward the end of twelth grade, only children who were planning to continue their education after high school were included in the analyses. With twice as many stepchildren not planning to pursue a postsecondary education (i.e., 8% of stepchildren vs. 4% present of genetic children), the total extent of parental bias against stepchildren may not have been captured with the measures used in this study. Third, through self-selection into the study, it is possible that the parental responses were confounded by the bias toward questionnaire completion by genetic parents [i.e., only 75 (10%) of the final 772 stepfamily respondents were actually stepparents]. Because only a small number of stepparents 4 These estimates are rough approximations. Due to the presence of open-ended categories, a decision was made to constrain the size of the open-ended intervals using the range of each variable’s preceding closed interval (e.g., the final category for educational savings was constrained to range from 30,001 to 45,000). The midpoint of each interval (in dollars for educational savings and expected investment; in years for financial preparation) was calculated to serve as the basis for rescaling the dependent variables. Using each variable’s new scale as input, the MANCOVA was rerun. Between-family type investment disparities were derived from the difference in each group’s mean investment on each of the dependent measures. 5 As alluded to in the next paragraph, the measures utilized in this study may not have tapped the extent to which postsecondary education actually is available to stepchildren. Because significantly more stepchildren drop out of high school and because significantly more stepchildren do not plan to continue their education after secondary schooling, the results of this study likely underestimate a stepchild’s actual opportunity for an attempt at attaining a postsecondary degree.
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completed the parent questionnaire, it is open to speculation whether the genetic parent responses in these families are reflective of stepparent intentions. Additional analyses (not presented) utilizing the small number of stepparents who did respond to the questionnaire revealed that stepparents reported lower mean levels of support on each educational investment indicator when considered relative to responses provided by stepfamily genetic parent participants. These within-family type reporting discrepancies were not statistically significant, but potentially imply that the effect of stepparent influence may be underestimated in the analyses presented.
CONCLUSION The present study provides some support for expectations derived from application of evolutionary logic. With control of several potential confounds, stepchildren were likely to receive less parental support for pursuit of postsecondary education, relative to children with two genetic parents. However, possibly due to sample exclusions, unmeasured displays of mating effort, and/or other limitations in the data source, these between-family type investment disparities were not large in magnitude. Nonetheless, because statistically significant between-family type investment differences still remain after the conservative analytic approach taken in this research, a concern is raised. By utilizing data derived from self-selected parental participants and by focusing the analysis only on children who received enough parental support to remain in school and have postsecondary educational aspirations, this study, although demonstrating nonchance between family-type investment disparities, is likely to have underestimated stepchildren’s relative disadvantage in gaining access to higher levels of education. Future investigation, with comprehensive, objective, and psychometrically sound measures, will be necessary to determine the true extent to which stepchildren face subtle and overt tactics of parental discrimination. This research was supported by a grant from the American Educational Research Association, which receives funds for its “AERA Grants Program” from the National Center for Education Statistics and the Office of Educational Research and Improvement (U.S. Department of Education) and the National Science Foundation under NSF Grant #RED-9452861. Opinions reflect those of the author and do not necessarily reflect those of the granting agencies. I would like to thank Martin Daly, Steven Gangestad, Candace Schau, Joseph Stevens, Margo Wilson, and two anonymous reviewers for helpful comments on earlier drafts of this paper. Any remaining conceptual, computational, or interpretational inaccuracies are solely the author’s responsibility.
REFERENCES Alexander, R.D. Darwinism and Human Affairs. Seattle: University of Washington Press, 1979. Anderson, E.R., and Rice, A.M. Sibling relationships during remarriage. In Coping with Marital Transitions, E.M. Hetherington and G.W. Clingempeel (Eds.). Monographs of the Society for Research in Child Development, 57 (Serial No. 227), 1992, pp. 149–177. Aquilino, W.S. Family structure and home leaving: a further specification of the relationship. Journal of Marriage and Family 53:999–1010, 1991.
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