Data analytic techniques for treatment outcome studies with pretest/posttest measurements: an extensive primer.

This paper discusses several data analytic technique, for examining treatment efficacy in pretest-posttest control group designs. The following approaches are described: ANOVA on post scores, ANOVA on difference scores, split-plot repeated measures ANOVA, profile analysis, and ANOCOVA with prescore as the co-variate. Guidelines for choosing between available techniques are provided; the primary focus here is on the nature of the null hypothesis, the assumptions underlying the approach, and the power of the procedure. The importance of examining the characteristics of the data set in selecting an analytic technique is illustrated.

[1]  G. Box.  Some Theorems on Quadratic Forms Applied in the Study of Analysis of Variance Problems, II. Effects of Inequality of Variance and of Correlation Between Errors in the Two-Way Classification , 1954 .

[2]  James Jaccard,et al.  Repeated Measures Analysis of Means in Clinical Research , 1985 .

[3]  M. Aldenderfer,et al.  Cluster Analysis. Sage University Paper Series On Quantitative Applications in the Social Sciences 07-044 , 1984 .

[4]  J H Ellenberg,et al.  Analysis of clinical trials by treatment actually received: is it really an option? , 1991, Statistics in medicine.

[5]  M K Kaiser,et al.  MANOVA method for analyzing repeated measures designs: an extensive primer. , 1985, Psychological bulletin.

[6]  H. Huynh,et al.  Estimation of the Box Correction for Degrees of Freedom from Sample Data in Randomized Block and Split-Plot Designs , 1976 .

[7]  S. Geisser,et al.  On methods in the analysis of profile data , 1959 .

[8]  Anthony S. Bryk,et al.  Application of Hierarchical Linear Models to Assessing Change , 1987 .

[9]  J. Stevens,et al.  Applied Multivariate Statistics for the Social Sciences , 1993 .

[10]  S D Imber,et al.  Some conceptual and statistical issues in analysis of longitudinal psychiatric data. Application to the NIMH treatment of Depression Collaborative Research Program dataset. , 1993, Archives of general psychiatry.

[11]  Bradley E. Huitema,et al.  The analysis of covariance and alternatives , 1980 .

[12]  S. Fiske,et al.  The Handbook of Social Psychology , 1935 .

[13]  Robert J. Boik,et al.  The mixed model for multivariate repeated measures: validity conditions and an approximate test , 1988 .

[14]  Scott E. Maxwell,et al.  Designing Experiments and Analyzing Data , 1991 .

[15]  B. Tabachnick,et al.  Using Multivariate Statistics , 1983 .

[16]  G. Glass,et al.  Statistical methods in education and psychology , 1970 .

[17]  Ellen R. Girden,et al.  ANOVA: Repeated Measures , 1991 .

[18]  Alan J. Klockars.  Evaluating Pretest-Posttest Control Group Experiments , 1992 .

[19]  D. Quade,et al.  Statistical analysis of repeated measures in psychiatric research. , 1990, Archives of general psychiatry.

[20]  J. Stevens.  Applied Multivariate Statistics for the Social Sciences , 1986 .

[21]  T. Micceri.  The unicorn, the normal curve, and other improbable creatures. , 1989 .

[22]  R. Malgady,et al.  Comparing the Reliability of Difference Scores and Residuals in Analysis of Covariance , 1991 .

[23]  Mitchell B. Karpman.  Comparing Two Non-Parallel Regression Lines with the Parametric Alternative to Analysis of Covariance Using SPSS-X or SAS—The Johnson-Neyman Technique , 1986 .

[24]  Stephen Warwick Looney,et al.  Exploratory Repeated Measures Analysis for Two or More Groups: Review and Update , 1989 .

[25]  R. Mclean,et al.  Using a repeated measures ANOVA to analyze the data from a pretest-posttest design : a potentially confusing task , 1975 .

[26]  Michael L. Davidson.  Univariate versus multivariate tests in repeated-measures experiments. , 1972 .