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Development and validation of a Biodata Inventory as an alternative method to measurement of the five factor model of personality
The Social Science Journal 44 (2007) 383–389
Development and validation of a Biodata Inventory as an alternative method to measurement of the five factor model of personality Howard Sisco a,∗ , Richard R. Reilly b a
New York City College of Technology, 300 Jay Street, Brooklyn, NY 11201-2983, United States b Stevens Institute of Technology, Castle Point, Hoboken, NJ, United States
Abstract The present study was designed to test the effectiveness of using a biographical inventory as an alternative to a traditional personality inventory in measuring the five factor model of personality. A combination of empirical and rational strategies were incorporated in the development and scoring of the biodata items. All (N = 383) participants completed the newly developed Biodata Inventory and the NEO-Five Factor Inventory. Confirmatory factor analysis was performed to examine the goodness of fit of the five factor structure from the respondents’ data. All participants completed a letter cancellation task, reported grade point averages, and SAT scores. Predictive validity was assessed for both instruments’ scores. Results indicate that the five factor model fit the data from the biodata and personality inventories. Predictive validities of both inventories’ scores were consistent with many other research results. The relationship of the Conscientiousness biodata scores to grade point average and task completion performance were statistically significant. © 2007 Elsevier Inc. All rights reserved.
1. Introduction The predictive validities of using personality measures as prognosticators of job performance (Barrick, Mount & Judge, 2001) have been improving. A comparatively new theoretical model of personality deserves considerable credit for this optimism. The five factor model of personality (FFM) is a cardinal postulated model for understanding the personality-job performance connection by most theorists. This model proposes that the structure of personality consists of ∗ Corresponding author. E-mail address: [email protected] (H. Sisco).
0362-3319/$ – see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.soscij.2007.03.010
384
H. Sisco, R.R. Reilly / The Social Science Journal 44 (2007) 383–389
five superordinate factors: Neuroticism, Extraversion, Openness to experience, Agreeableness, and Conscientiousness (Digman, 1990). The FFM has provided researchers with a common framework in which to organize and direct studies (Barrick & Mount, 1991). Investigations conducted within the framework of the FFM have shown certain personality traits (e.g., Conscientiousness) to be dependable predictors of job performance criteria across many occupations, organizations, industries, and cultures (e.g., Barrick & Mount, 1991; Salgado, 1997; Hurtz & Donovan, 2000).
2. Faking and social desirability on personality and biodata inventories Hollenbeck and Whitner (1988) argued that self-report personality inventories have dominated research and practice in the area of personnel selection without merit. They suggested that future researchers and practitioners should depend less on flawed techniques to curtail problems that may occur in employment context. For example, many organizations use a self-report personality inventory in which prospective job applicants answer multiple choice questions on how they would behave in an imagined hypothetical situation. This selection technique enhances the opportunity for faking and social desirable responding. Research results have continued to increase enthusiasm for the use of biodata as a selection tool and as an alternative to personality inventories (e.g., Stricker & Rock, 1998). The main tenet underlying the use of biodata is that past behavior is one of the best predictors of future behavior. Many organizations include a biographical inventory in their selection battery. Biodata items are collected from individuals who report characteristic behaviors or experiences in a particular situation that have occurred previously in their lives (Mumford & Owens, 1987). “Faking good” on biodata items require conscious lying because biodata items’ measures are more directed to past experiences than hypothetical events (Mael, 1991). The primary objectives of this research were to (a) develop a biographical instrument that measures individual personality differences within a framework of the FFM, (b) investigate the discriminant and convergent validities of the biodata measures, and (c) to examine the predictive validity of a biodata predictor. Accordingly, the hypotheses are: (1) Confirmatory factor analysis will demonstrate that the FFM of personality best describes a subject’s responses on the Biodata Inventory and the NEO-FFI. (2) Participants’ scores for Conscientiousness on both inventories would be positively related to performance on the letter cancellation task and to grade point average.
3. Method 3.1. Phase I: Biodata Inventory development Most of the biographical items were developed with a strategy similar to the constructbased approach supported by Mumford and Stokes (1992). A group of eight graduate
H. Sisco, R.R. Reilly / The Social Science Journal 44 (2007) 383–389
385
psychology students generated a set of background items that corresponded to clear and precise definitions for each of the FFM constructs. Generation goals for at least 20 items per factor were met. A total of 220 original items were generated: Neuroticism, 37 items; Extraversion, 51 items; Openness, 38 items; Agreeableness, 32 items; Conscientiousness: 62 items. Upon completion of gathering and generating biodata items, 23 judges were presented with a randomized list of the items, provided with the conceptual definition of each of the FFM constructs, and asked to classify the items into the five factor categories, or a sixth, not applicable category. Analysis of variance was performed on each one of the 220 biodata items. Each item’s response option served as a level for the independent variable. Factor scores on the NEO-FFI for each hypothesized dimension served as the dependent variable. Only 155 items with significant F scores were retained. After response options were assigned scores, a reliability analysis was conducted on the newly weighted biodata items. The 155 items were aggregated into groups consisting of only items hypothesized for that factor. Each of these five groups were subjected to a separate reliability analysis. Squared multiple correlations for each item were examined to determine which item contributed the most weight to the total reliability score. The goal was to retain the most reliable 20 item scores per factor. This was the case for Neuroticism, Extraversion, Conscientiousness and Agreeableness. Openness had only 15 items that met the arbitrary criteria R2 > 0.10 assigned by the researchers. This left the final biodata scale a total of 95 items to be validated. Reliabilities for the biodata factors ranged from 0.56 to 0.83 for the sample (Neuroticism = 0.72; Extraversion = 0.83; Openness = 0.64; Agreeableness = 0.56; Conscientiousness = 0.75). 3.2. Phase II—stage 1: scale validation Scale validation was conducted in two stages. The first stage in the research was the assessment of the number of factors the biodata scale measures. Two confirmatory factor analyses were performed on the response data from both the NEO-FFI and Biodata Inventory. 3.3. Participants Three hundred and eighty-three participants took part in the study. All participants were recruited from psychology classes at two New Jersey state universities. The participants received a small amount of credit toward their course grade.
4. Measures 4.1. NEO-FFI—an inventory measure of the five factor model The NEO-FFI consists of 60 items that have a five-point Likert scale response option: strongly agree to strongly disagree. Total scores for Neuroticism, Extraversion, Openness, Conscientiousness, and Agreeableness are derived from 12 items each.
386
H. Sisco, R.R. Reilly / The Social Science Journal 44 (2007) 383–389
Reliabilities for the present study ranged from 0.66 to 0.91 (Neuroticism = 0.89; Extraversion = 0.79; Openness = 0.66; Agreeableness = 0.69; Conscientiousness = 0.91. Coefficient Alpha for the complete scale = 0.70). 4.2. Stage II: establishing criterion-related validity The second stage was to correlate Conscientiousness factor scores on both instruments with external criterion measures. A letter cancellation task was chosen because it did not appear influenced by prior differences in cognitive ability. The task seemed sufficiently repetitive and boring to assume that a subject’s success would reflect higher degrees of conscientiousness. 5. Criterion measures Test booklets developed by researchers were the accouterment used for this task. The pages of these booklets each contained ten lines of 45 capital letters and the individual lines consisted of 21 runs of letters randomly arranged. Ranging from one to five letters, a “run” is a series of repeated letters consecutively placed. For example, XXLMMMMM, which represents three runs: the first run, being the X’s, has a length of two, the center run, “L”, is a single letter run, and finally, the last run, consisting of M’s, has a length of five. During the completion of the Letter Cancellation Task, it is imperative that each subject places a slash at the onset of every new run. The participants are not informed of the line totals and are asked to continue to the following line until directed to stop. Further criterion-related validity was established by obtaining subject’s cumulative college grade point averages and most recent SAT scores. This was done to assess the predictive strength of Conscientiousness factor score (Digman & Takemoto-Chock, 1981). 6. Procedure Participants were handed an envelope that contained a demographic questionnaire, NEOFFI, Biodata Inventory, an answer sheet, letter cancellation task booklet and a 14 item postexperimental survey that served as a manipulations check. In small groups of between 25 and 40 subjects, participants were administered the Biodata Inventory, NEO-FFI, and the letter cancellation task in the same time period. Administration of all measures was counterbalanced to help control for carryover effects. Participants were given 20 min to complete the letter cancellation task. They were not told how much time that they would have. The instructions for completing both scales stressed the importance of responding candidly and honestly for research purposes. 7. Results Means, standard deviations and correlations for the NEO-FFI and Biodata Inventories are presented in Table 1. Mean scores for the NEO-FFI scales were within range of the scores
Variable
Mean
S.D.
1
NEO-FFI Neuroticism Extraversion Openness Agreeableness Conscientiousness
22.06 31.39 29.48 32.08 32.60
8.94 6.12 5.86 6.18 7.77
– −0.32*** −0.09 −0.24*** −0.46***
– 0.08 0.29*** 0.39***
Biodata Inventory Neuroticism Extraversion Openness Agreeableness Conscientiousness
38.99 47.70 35.80 48.37 49.02
11.41 10.39 8.48 8.61 10.42
0.65*** −0.21*** −0.10 −0.24 −0.37***
−0.19*** 0.59*** 0.16* 0.22*** 0.36
Note: N = 325–371. Convergent correlations are bold faced. ∗ p < 0.05. ∗∗ p < 0.01. ∗∗∗ p < 0.0.
2
3
– 0.03 0.03 −0.06* 0.10 0.58*** −0.01 0.17***
4
– 0.22*** −0.17*** −0.01 0.07 0.47*** 0.17***
5
6
7
– −0.11 −0.02 0.01 −0.28***
– 0.23*** 0.15** 0.28***
8
9
– −0.29*** 0.12* 0.11 0.09 0.59***
– 15** 0.29***
0.29***
H. Sisco, R.R. Reilly / The Social Science Journal 44 (2007) 383–389
Table 1 Means, standard deviations, and correlations for NEO-FFI and Biodata Inventory factor scores
387
388
H. Sisco, R.R. Reilly / The Social Science Journal 44 (2007) 383–389
for college aged participants reported in the test manual. Intercorrelations of the NEO-FFI scales were comparable with prior findings (Costa & McCrae, 1992). Correlations between the Biodata Inventory and NEO-FFI scales demonstrate convergent validity for those common factors scores. Low intercorrelations between different factors scores on both measures indicate acceptable discriminant validity. The five factor model fit the data well for the NEO-FFI. The results for goodness of fit statistics computed were Chi square, χ2 (105, n = 345) = 2021.18, Goodness fit index (GFI) = 0.94 root mean square residual (RMSR = 0.43), and a comparative fit index (CFI) = 0.94. The nonnormed fit index (NNFI) was 0.92, and incremental fit index (IFI) = 0.94. The five factor solution accounted for 71.4% of the variance on the NEO-FFI. Results of confirmatory factor analysis on the Biodata Inventory also supported a good fit for the five factor solution. This fit was evidenced by a Chi square χ2 (105, n = 345) = 1469.25, CFI = 0.92, GFI = 0.94 and a RMSR = 0.95. The two incremental measures also demonstrated a good fit for the five factor model to the data, NNFI = 0.90, and IFI = 0.92. The five factor solution accounted for 66% of the variance on the biodata scale. Criterion-related validity of both instruments’ scores was examined by calculating a Pearson product moment correlation coefficient between each factor score and criterion measure. As predicted, the biodata Conscientious factor score was statistically significant correlated (r = 0.20), p < 0.001, with task performance, and (r = 0.39), p < 0.001, with GPA, but not with (r = 0.06) SAT. Similarly, the NEO-FFI Conscientiousness factor score demonstrated a positive relationship with (r = 0.23), p < 0.001 task performance (r = 0.29), p < 0.001 GPA, but not (0.00) SAT. Correlations were subjected to a test of significant of difference for dependent correlations between Conscientiousness and each criterion. Results indicated a statistically non-significant difference in the correlations for conscientiousness on both scales: GPA, t(376) = 0.45; task, t(367) = −0.74, and SAT (367) = 1.21. Two other biodata factor scores were statistically significant correlated to GPA, Extraversion (r = −0.12, p < 0.05) and Neuroticism (r = −0.11, p < 0.05). Openness was the only other biodata factor score to correlate significantly with a performance measure in this sample (r = 0.16), p < 0.05 with SAT. NEO-FFI Openness factor also showed a statistically significant relationship to (r = 0.19), p < 0.01 SAT scores.
8. Discussion Results of the confirmatory factor analysis provide strong evidence of the convergent and discriminant validity of the Biodata Inventory scores. As predicted, the biodata items loaded on their hypothesized factors. Five latent factors accounted for a substantial portion of variance. Overall fit of the five factor model was good (i.e., over 0.90) as measured by several goodness of fit indices. This suggests that there are not any statistically significant cross-loading of items on the non-hypothesized factors. A bivariate correlation matrix between the Biodata and NEO-FFI scales’ scores provided further evidence for convergent and discriminant construct validity. Specifically, overall biodata factor scores correlated with intended factors at a range of 0.47–0.65 with a mean correlation = 0.57 demonstrating convergent validity. Discriminant validity of the factor scores was supported by correlations between all uncommon factor scores falling below 0.40. In addition,
H. Sisco, R.R. Reilly / The Social Science Journal 44 (2007) 383–389
389
support was found for conscientiousness scores as a valid predictor of letter task performance and GPA.
References Barrick, M. R., & Mount, M. K. (1991). The big five personality dimensions and job performance: A meta-analysis. Personnel Psychology, 44, 1–26. Barrick, M. R., Mount, M. K., & Judge, T. A. (2001). Personality and performance at the beginning of the new millennium: What do we know and where do we go next? International Journal of Selection and Assessment, 9, 9–30. Costa, P. T., Jr., & McCrae, R. R. (1992). The NEO personality inventory (NEO-PI-R) and NEO five factor inventory (NEO-FFI) professional manual. Odessa, FL: Psychological Assessment Resources. Digman, J. M. (1990). Personality structure: Emergence of the five-factor model. Annual Review of Psychology, 41, 417–440. Digman, J. M., & Takemoto-Chock, N. K. (1981). Factors in the natural language of personality: Re-analysis and comparison of six major studies. Multivariate Behavioral Research, 16, 146–170. Hollenbeck, J. R., & Whitner, E. M. (1988). Reclaiming personality traits for personnel selection: Self-esteem as an illustrative case. Journal of Management, 14(1), 81–91. Hurtz, G. M., & Donovan, J. J. (2000). Personality and job performance: the big five revisited. Journal of Applied Psychology, 85, 869–879. Mael, F. A. (1991). A conceptual rationale for the domain and attributes of biodata items. Personnel Psychology, 44, 763–792. Mumford, M. D., & Owens, W. A. (1987). Methodology review: Principles, procedures, and findings in the application of background data measures. Applied Psychological Measurement, 11(1), 1–31. Mumford, M. D., & Stokes, G. S. (1992). Developmental determinants of Individual action: Theory and practice in applying background measures. In M. D. Dunnette (Ed.), Handbook of Industrial and Organizational Psychology (2nd ed., vol. 3, pp. 61–138). Palo Alto, CA: Consulting Psychologists Press. Salgado, J. F. (1997). The factor model of personality and job performance in the European community. Journal of Applied Psychology, 82(1), 30–43. Stricker, L. J., & Rock, D. A. (1998). Assessing leadership potential with a biographical measure of personality traits. International Journal of Selection Assessment, 6, 164–184.
Development and validation of a Biodata Inventory as an alternative method to measurement of the five factor model of personality Howard Sisco a,∗ , Richard R. Reilly b a
New York City College of Technology, 300 Jay Street, Brooklyn, NY 11201-2983, United States b Stevens Institute of Technology, Castle Point, Hoboken, NJ, United States
Abstract The present study was designed to test the effectiveness of using a biographical inventory as an alternative to a traditional personality inventory in measuring the five factor model of personality. A combination of empirical and rational strategies were incorporated in the development and scoring of the biodata items. All (N = 383) participants completed the newly developed Biodata Inventory and the NEO-Five Factor Inventory. Confirmatory factor analysis was performed to examine the goodness of fit of the five factor structure from the respondents’ data. All participants completed a letter cancellation task, reported grade point averages, and SAT scores. Predictive validity was assessed for both instruments’ scores. Results indicate that the five factor model fit the data from the biodata and personality inventories. Predictive validities of both inventories’ scores were consistent with many other research results. The relationship of the Conscientiousness biodata scores to grade point average and task completion performance were statistically significant. © 2007 Elsevier Inc. All rights reserved.
1. Introduction The predictive validities of using personality measures as prognosticators of job performance (Barrick, Mount & Judge, 2001) have been improving. A comparatively new theoretical model of personality deserves considerable credit for this optimism. The five factor model of personality (FFM) is a cardinal postulated model for understanding the personality-job performance connection by most theorists. This model proposes that the structure of personality consists of ∗ Corresponding author. E-mail address: [email protected] (H. Sisco).
0362-3319/$ – see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.soscij.2007.03.010
384
H. Sisco, R.R. Reilly / The Social Science Journal 44 (2007) 383–389
five superordinate factors: Neuroticism, Extraversion, Openness to experience, Agreeableness, and Conscientiousness (Digman, 1990). The FFM has provided researchers with a common framework in which to organize and direct studies (Barrick & Mount, 1991). Investigations conducted within the framework of the FFM have shown certain personality traits (e.g., Conscientiousness) to be dependable predictors of job performance criteria across many occupations, organizations, industries, and cultures (e.g., Barrick & Mount, 1991; Salgado, 1997; Hurtz & Donovan, 2000).
2. Faking and social desirability on personality and biodata inventories Hollenbeck and Whitner (1988) argued that self-report personality inventories have dominated research and practice in the area of personnel selection without merit. They suggested that future researchers and practitioners should depend less on flawed techniques to curtail problems that may occur in employment context. For example, many organizations use a self-report personality inventory in which prospective job applicants answer multiple choice questions on how they would behave in an imagined hypothetical situation. This selection technique enhances the opportunity for faking and social desirable responding. Research results have continued to increase enthusiasm for the use of biodata as a selection tool and as an alternative to personality inventories (e.g., Stricker & Rock, 1998). The main tenet underlying the use of biodata is that past behavior is one of the best predictors of future behavior. Many organizations include a biographical inventory in their selection battery. Biodata items are collected from individuals who report characteristic behaviors or experiences in a particular situation that have occurred previously in their lives (Mumford & Owens, 1987). “Faking good” on biodata items require conscious lying because biodata items’ measures are more directed to past experiences than hypothetical events (Mael, 1991). The primary objectives of this research were to (a) develop a biographical instrument that measures individual personality differences within a framework of the FFM, (b) investigate the discriminant and convergent validities of the biodata measures, and (c) to examine the predictive validity of a biodata predictor. Accordingly, the hypotheses are: (1) Confirmatory factor analysis will demonstrate that the FFM of personality best describes a subject’s responses on the Biodata Inventory and the NEO-FFI. (2) Participants’ scores for Conscientiousness on both inventories would be positively related to performance on the letter cancellation task and to grade point average.
3. Method 3.1. Phase I: Biodata Inventory development Most of the biographical items were developed with a strategy similar to the constructbased approach supported by Mumford and Stokes (1992). A group of eight graduate
H. Sisco, R.R. Reilly / The Social Science Journal 44 (2007) 383–389
385
psychology students generated a set of background items that corresponded to clear and precise definitions for each of the FFM constructs. Generation goals for at least 20 items per factor were met. A total of 220 original items were generated: Neuroticism, 37 items; Extraversion, 51 items; Openness, 38 items; Agreeableness, 32 items; Conscientiousness: 62 items. Upon completion of gathering and generating biodata items, 23 judges were presented with a randomized list of the items, provided with the conceptual definition of each of the FFM constructs, and asked to classify the items into the five factor categories, or a sixth, not applicable category. Analysis of variance was performed on each one of the 220 biodata items. Each item’s response option served as a level for the independent variable. Factor scores on the NEO-FFI for each hypothesized dimension served as the dependent variable. Only 155 items with significant F scores were retained. After response options were assigned scores, a reliability analysis was conducted on the newly weighted biodata items. The 155 items were aggregated into groups consisting of only items hypothesized for that factor. Each of these five groups were subjected to a separate reliability analysis. Squared multiple correlations for each item were examined to determine which item contributed the most weight to the total reliability score. The goal was to retain the most reliable 20 item scores per factor. This was the case for Neuroticism, Extraversion, Conscientiousness and Agreeableness. Openness had only 15 items that met the arbitrary criteria R2 > 0.10 assigned by the researchers. This left the final biodata scale a total of 95 items to be validated. Reliabilities for the biodata factors ranged from 0.56 to 0.83 for the sample (Neuroticism = 0.72; Extraversion = 0.83; Openness = 0.64; Agreeableness = 0.56; Conscientiousness = 0.75). 3.2. Phase II—stage 1: scale validation Scale validation was conducted in two stages. The first stage in the research was the assessment of the number of factors the biodata scale measures. Two confirmatory factor analyses were performed on the response data from both the NEO-FFI and Biodata Inventory. 3.3. Participants Three hundred and eighty-three participants took part in the study. All participants were recruited from psychology classes at two New Jersey state universities. The participants received a small amount of credit toward their course grade.
4. Measures 4.1. NEO-FFI—an inventory measure of the five factor model The NEO-FFI consists of 60 items that have a five-point Likert scale response option: strongly agree to strongly disagree. Total scores for Neuroticism, Extraversion, Openness, Conscientiousness, and Agreeableness are derived from 12 items each.
386
H. Sisco, R.R. Reilly / The Social Science Journal 44 (2007) 383–389
Reliabilities for the present study ranged from 0.66 to 0.91 (Neuroticism = 0.89; Extraversion = 0.79; Openness = 0.66; Agreeableness = 0.69; Conscientiousness = 0.91. Coefficient Alpha for the complete scale = 0.70). 4.2. Stage II: establishing criterion-related validity The second stage was to correlate Conscientiousness factor scores on both instruments with external criterion measures. A letter cancellation task was chosen because it did not appear influenced by prior differences in cognitive ability. The task seemed sufficiently repetitive and boring to assume that a subject’s success would reflect higher degrees of conscientiousness. 5. Criterion measures Test booklets developed by researchers were the accouterment used for this task. The pages of these booklets each contained ten lines of 45 capital letters and the individual lines consisted of 21 runs of letters randomly arranged. Ranging from one to five letters, a “run” is a series of repeated letters consecutively placed. For example, XXLMMMMM, which represents three runs: the first run, being the X’s, has a length of two, the center run, “L”, is a single letter run, and finally, the last run, consisting of M’s, has a length of five. During the completion of the Letter Cancellation Task, it is imperative that each subject places a slash at the onset of every new run. The participants are not informed of the line totals and are asked to continue to the following line until directed to stop. Further criterion-related validity was established by obtaining subject’s cumulative college grade point averages and most recent SAT scores. This was done to assess the predictive strength of Conscientiousness factor score (Digman & Takemoto-Chock, 1981). 6. Procedure Participants were handed an envelope that contained a demographic questionnaire, NEOFFI, Biodata Inventory, an answer sheet, letter cancellation task booklet and a 14 item postexperimental survey that served as a manipulations check. In small groups of between 25 and 40 subjects, participants were administered the Biodata Inventory, NEO-FFI, and the letter cancellation task in the same time period. Administration of all measures was counterbalanced to help control for carryover effects. Participants were given 20 min to complete the letter cancellation task. They were not told how much time that they would have. The instructions for completing both scales stressed the importance of responding candidly and honestly for research purposes. 7. Results Means, standard deviations and correlations for the NEO-FFI and Biodata Inventories are presented in Table 1. Mean scores for the NEO-FFI scales were within range of the scores
Variable
Mean
S.D.
1
NEO-FFI Neuroticism Extraversion Openness Agreeableness Conscientiousness
22.06 31.39 29.48 32.08 32.60
8.94 6.12 5.86 6.18 7.77
– −0.32*** −0.09 −0.24*** −0.46***
– 0.08 0.29*** 0.39***
Biodata Inventory Neuroticism Extraversion Openness Agreeableness Conscientiousness
38.99 47.70 35.80 48.37 49.02
11.41 10.39 8.48 8.61 10.42
0.65*** −0.21*** −0.10 −0.24 −0.37***
−0.19*** 0.59*** 0.16* 0.22*** 0.36
Note: N = 325–371. Convergent correlations are bold faced. ∗ p < 0.05. ∗∗ p < 0.01. ∗∗∗ p < 0.0.
2
3
– 0.03 0.03 −0.06* 0.10 0.58*** −0.01 0.17***
4
– 0.22*** −0.17*** −0.01 0.07 0.47*** 0.17***
5
6
7
– −0.11 −0.02 0.01 −0.28***
– 0.23*** 0.15** 0.28***
8
9
– −0.29*** 0.12* 0.11 0.09 0.59***
– 15** 0.29***
0.29***
H. Sisco, R.R. Reilly / The Social Science Journal 44 (2007) 383–389
Table 1 Means, standard deviations, and correlations for NEO-FFI and Biodata Inventory factor scores
387
388
H. Sisco, R.R. Reilly / The Social Science Journal 44 (2007) 383–389
for college aged participants reported in the test manual. Intercorrelations of the NEO-FFI scales were comparable with prior findings (Costa & McCrae, 1992). Correlations between the Biodata Inventory and NEO-FFI scales demonstrate convergent validity for those common factors scores. Low intercorrelations between different factors scores on both measures indicate acceptable discriminant validity. The five factor model fit the data well for the NEO-FFI. The results for goodness of fit statistics computed were Chi square, χ2 (105, n = 345) = 2021.18, Goodness fit index (GFI) = 0.94 root mean square residual (RMSR = 0.43), and a comparative fit index (CFI) = 0.94. The nonnormed fit index (NNFI) was 0.92, and incremental fit index (IFI) = 0.94. The five factor solution accounted for 71.4% of the variance on the NEO-FFI. Results of confirmatory factor analysis on the Biodata Inventory also supported a good fit for the five factor solution. This fit was evidenced by a Chi square χ2 (105, n = 345) = 1469.25, CFI = 0.92, GFI = 0.94 and a RMSR = 0.95. The two incremental measures also demonstrated a good fit for the five factor model to the data, NNFI = 0.90, and IFI = 0.92. The five factor solution accounted for 66% of the variance on the biodata scale. Criterion-related validity of both instruments’ scores was examined by calculating a Pearson product moment correlation coefficient between each factor score and criterion measure. As predicted, the biodata Conscientious factor score was statistically significant correlated (r = 0.20), p < 0.001, with task performance, and (r = 0.39), p < 0.001, with GPA, but not with (r = 0.06) SAT. Similarly, the NEO-FFI Conscientiousness factor score demonstrated a positive relationship with (r = 0.23), p < 0.001 task performance (r = 0.29), p < 0.001 GPA, but not (0.00) SAT. Correlations were subjected to a test of significant of difference for dependent correlations between Conscientiousness and each criterion. Results indicated a statistically non-significant difference in the correlations for conscientiousness on both scales: GPA, t(376) = 0.45; task, t(367) = −0.74, and SAT (367) = 1.21. Two other biodata factor scores were statistically significant correlated to GPA, Extraversion (r = −0.12, p < 0.05) and Neuroticism (r = −0.11, p < 0.05). Openness was the only other biodata factor score to correlate significantly with a performance measure in this sample (r = 0.16), p < 0.05 with SAT. NEO-FFI Openness factor also showed a statistically significant relationship to (r = 0.19), p < 0.01 SAT scores.
8. Discussion Results of the confirmatory factor analysis provide strong evidence of the convergent and discriminant validity of the Biodata Inventory scores. As predicted, the biodata items loaded on their hypothesized factors. Five latent factors accounted for a substantial portion of variance. Overall fit of the five factor model was good (i.e., over 0.90) as measured by several goodness of fit indices. This suggests that there are not any statistically significant cross-loading of items on the non-hypothesized factors. A bivariate correlation matrix between the Biodata and NEO-FFI scales’ scores provided further evidence for convergent and discriminant construct validity. Specifically, overall biodata factor scores correlated with intended factors at a range of 0.47–0.65 with a mean correlation = 0.57 demonstrating convergent validity. Discriminant validity of the factor scores was supported by correlations between all uncommon factor scores falling below 0.40. In addition,
H. Sisco, R.R. Reilly / The Social Science Journal 44 (2007) 383–389
389
support was found for conscientiousness scores as a valid predictor of letter task performance and GPA.
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