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A34 Factor analytic strategies for evaluating generalizability of construct validity
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Abstracts
A34 FACTOR ANALYTIC STRATEGIES FOR EVALUATING GENERALIZABILITY OF CONSTRUCT VALIDITY
John E. Cornell, Cindy P. Mulrow, Helen P. Hazuda, Jacqueline A. Pugh, and Michael P. Stern
Audie L. Murphy Veterans Hospital San Antonio, Texas
Construct validity is not necessarily generalizable from one population to another, particularly when the instrument has been altered to make it accessible and/or relevant to the new population. Apparent content validity does not provide sufficient information to assume generalizability of construct validity. Multi-modal, simultaneous, and confirmatory factor analytic techniques are powerful analytic methods for evaluating the generalizability of construct validity across populations. The first two techniques combine subjects' responses across populations to elucidate the instrument's common conceptual structure. Confirmatory techniques evaluate the fit of subject's responses within a particular population to the instrument's established conceptual structure. The paper discusses the conceptual rationale and application of these factor analytic techniques to evaluate generalizability of construct validity. Sickness Impact Profile data obtained on three distinct samples--Diabetics identified within the San Antonio Heart Study Cohorts, Renal Dialysis patients from a case-control study, and Frail Elder Nursing Home participants in a controlled clinical trial--are used to illustrate the application and interpretation of these techniques. A35 COMPARISON OF ANALYTICAL METHODS WHEN RESPONSE FLUCTUATES BETWEEN SUCCESS AND FAILURE Kathryn L. P. Linton, Mei-Ying Lai and Stanley P. Azen
University of Southern California Los Angeles, California The Silicone Study, a multi-center randomized, controlled clinical trial, was conducted to ascertain which of silicone oil and long-acting gas is the preferred tamponade in eyes undergoing vitrectomy for retinal detachment complicated by severe proliferative vitreoretinopathy. The primary outcome, "good" visual acuity, was measured at 7 time periods after the initial surgery. Since the vision of the patient often fluctuated between "good" and "poor," traditional methods of analyses generally do not accommodate these data. We compared four analytical methods originally developed to handle longitudinal data, namely, a traditional Mantel-Haenszel time to first event approach, a transition analysis, a growth-curve approach and a generalized estimating equation analysis. Through simulation experiments, we show the benefits and limitations of each method and provide recommendations for its use. Finally, we apply these methods to data arising from the Silicone Study. A36 ANALYSIS OF LONG TERM ADVERSE EXPERIENCE DATA USING THE WEIBULL MODEL Deborah R. Shapiro and Thomas J. Cook
Merck Research Laboratories Rahway, New Jersey For most drugs studied by pharmaceutical companies, the comparative period of a clinical trial is relatively short. To accumulate safety experience especially for drugs meant for chronic administration, trials are continued into "open extensions" in which all patients receive the experimental compound for several years. The information collected on adverse experiences (AEs) is usually tabulated as an overall crude rate. Survival analysis is more appropriate for the analysis of long term d~t8 and data with variable follow-up time, and provides richer information than a crude rate. The use of the Weibull model for the analysis of adverse experience data is presented and compared to nonparametric survival analytic techniques. Examples of parametric and nonparametric techniques are provided. Use of Weibull models to analyze AE data provide more accurate estimates of cumulative rates and provide a means to test whether or not these rates are increasing, constant, or decreasing with time.
Abstracts
A34 FACTOR ANALYTIC STRATEGIES FOR EVALUATING GENERALIZABILITY OF CONSTRUCT VALIDITY
John E. Cornell, Cindy P. Mulrow, Helen P. Hazuda, Jacqueline A. Pugh, and Michael P. Stern
Audie L. Murphy Veterans Hospital San Antonio, Texas
Construct validity is not necessarily generalizable from one population to another, particularly when the instrument has been altered to make it accessible and/or relevant to the new population. Apparent content validity does not provide sufficient information to assume generalizability of construct validity. Multi-modal, simultaneous, and confirmatory factor analytic techniques are powerful analytic methods for evaluating the generalizability of construct validity across populations. The first two techniques combine subjects' responses across populations to elucidate the instrument's common conceptual structure. Confirmatory techniques evaluate the fit of subject's responses within a particular population to the instrument's established conceptual structure. The paper discusses the conceptual rationale and application of these factor analytic techniques to evaluate generalizability of construct validity. Sickness Impact Profile data obtained on three distinct samples--Diabetics identified within the San Antonio Heart Study Cohorts, Renal Dialysis patients from a case-control study, and Frail Elder Nursing Home participants in a controlled clinical trial--are used to illustrate the application and interpretation of these techniques. A35 COMPARISON OF ANALYTICAL METHODS WHEN RESPONSE FLUCTUATES BETWEEN SUCCESS AND FAILURE Kathryn L. P. Linton, Mei-Ying Lai and Stanley P. Azen
University of Southern California Los Angeles, California The Silicone Study, a multi-center randomized, controlled clinical trial, was conducted to ascertain which of silicone oil and long-acting gas is the preferred tamponade in eyes undergoing vitrectomy for retinal detachment complicated by severe proliferative vitreoretinopathy. The primary outcome, "good" visual acuity, was measured at 7 time periods after the initial surgery. Since the vision of the patient often fluctuated between "good" and "poor," traditional methods of analyses generally do not accommodate these data. We compared four analytical methods originally developed to handle longitudinal data, namely, a traditional Mantel-Haenszel time to first event approach, a transition analysis, a growth-curve approach and a generalized estimating equation analysis. Through simulation experiments, we show the benefits and limitations of each method and provide recommendations for its use. Finally, we apply these methods to data arising from the Silicone Study. A36 ANALYSIS OF LONG TERM ADVERSE EXPERIENCE DATA USING THE WEIBULL MODEL Deborah R. Shapiro and Thomas J. Cook
Merck Research Laboratories Rahway, New Jersey For most drugs studied by pharmaceutical companies, the comparative period of a clinical trial is relatively short. To accumulate safety experience especially for drugs meant for chronic administration, trials are continued into "open extensions" in which all patients receive the experimental compound for several years. The information collected on adverse experiences (AEs) is usually tabulated as an overall crude rate. Survival analysis is more appropriate for the analysis of long term d~t8 and data with variable follow-up time, and provides richer information than a crude rate. The use of the Weibull model for the analysis of adverse experience data is presented and compared to nonparametric survival analytic techniques. Examples of parametric and nonparametric techniques are provided. Use of Weibull models to analyze AE data provide more accurate estimates of cumulative rates and provide a means to test whether or not these rates are increasing, constant, or decreasing with time.