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Abstract

Analysis of covariance is a useful statistical procedure for data analysis even when carefully executed random assignment procedures are employed. Statistically adjusting for the effects of the covariates on the outcome can help account for pretreatment group differences—even with careful sampling. In addition, analysis of covariance can increase statistical power, thus reducing the Type II error rate. This paper uses diagrams to show how analysis of covariance manipulates data under a variety of conditions. Also discussed are the relationship between analysis of covariance and statistical power and issues related to covariate selection. Finally, a simulated data analysis is used to demonstrate the process of selecting covariates and to show the results with and without statistically adjusting for the effects of the covariate.

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References

Barnett, W.S. , Escobar, C.M. , & Ravsten, M. (1988). Parent and clinic early intervention for children with language handicaps: A cost-effective analysis. Journal of the Division for Early Childhood, 12, 290–298.

Casto, G. , White, K.R. , & Taylor, C. (1983). Annual report of 1982–83 workscope for the early intervention research institute (U.S. Department of Education, Washington, DC, Contract No. 300-82-0367). Logan, UT: Early Intervention Research Institute.

Cochran, W.G. (1957). Analysis of covariance: Its nature and uses. Biometrics, 13, 261–281.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.

Eiserman, W.D. , McCoun, M. , & Escobar, C.M. (1990). A cost-effective analysis of two alternative program models for serving speech disordered preschoolers. Journal of Early Intervention, 14, 287–317.

Elashoff, J.D. (1969). Analysis of covariance: A delicate instrument. American Educational Research Journal, 6, 383–401.

Glass, G.V. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher, 5(10), 3–8.

Glass, G.V. , & Hopkins, K.D. (1984). Statistical methods in education and psychology (2nd ed.). Englewood Cliffs, NJ: Prentice-Hall.

Glass, G.V. , Peckham, P.D. , & Sanders, J.R. (1972). Consequences of failure to meet assumptions underlying the fixed effects analysis of variance and covariance. Review of Educational Research, 42, 237–288.

10.

Kirk, R.E. (1982). Analysis of covariance. In R.E. Kirk (Ed.), Experimental design: Procedures for the behavioral sciences (pp. 715–757). Belmot CA: Wadsworth Inc.

11.

Loehlin, J.C. (1992). Latent variable models: An introduction to factor, path, and structural analysis (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.

12.

Mehran, M. , & White, K.R. (1988). Parent tutoring as a supplement to compensatory education for first grade children. Remedial and Special Education, 9(3), 35–41.

13.

Taylor, M.J. , & White, K.R. (1992). An evaluation of alternative methods for computing standardized mean difference effect sizes. Journal of Experimental Education, 61, 63–72.

14.

Tukey, J.W. (1977). Exploratory data analysis. Philippines: Addison-Wesley.

15.

White, K.R. (Ed.) (1991). 1985–1991 final report of the longitudinal studies of the effects and costs of early intervention with handicapped children (U.S. Department of Education, Washington, DC, Contract No. 300-85-0173). Logan, UT: Early Intervention Research Institute.

Why Covariance? A Rationale for Using Analysis of Covariance Procedures in Randomized Studies

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