The Value of Cause and Effect Analysis in Developing Ability to Recognize Cause and Effect Relationships

Researchers in the behavioral sciences have utilized “ANOVA theory” to test research hypotheses ever since R. A. Fisher first derived the solution. There are, however, limitations to classical ANOVA, particularly with respect to the handling of unbalanced design, continuous independent variables, and multiple covariates. Further, classical ANOVA fails to provide a strength of relationship index. The authors provide evidence which demonstrates that ANOVA is a special case of a multivariate procedure termed “multiple regression.” Because multiple regression is the more general method, it is capable of handling data which have traditionally been a nemesis for ANOVA researchers. Since multiple regression is a more powerful method of statistical analysis, and since it also provides a strength of relationship index, the authors argue that it be used in place of ANOVA in educational research. Also discussed is the coding of categorical variables as well as available computer programs for multiple regression.