Multiple regression in behavioral research Elazar J. Pedhazur
Publisher: Wadsworth Publishing

They took turns to read and rate the responses of In view of the many significant relationships in the above univariate tests, we used multiple regression analyses to determine the parental characteristics that could predict child outcome variables. Cohen, J., Cohen, P., West, S.G. New York: Holt, Rinehart, & Winston. Multiple regression in behavioral research: Prediction and explanation (3rd ed.). Applied multiple regression/correlation analysis for the behavioral sci-ences (3rd ed.). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences, Edn. Further research examined the relationships between exercise regulations and various motivational consequences (i.e., behavioral intention, effort and importance associated with exercise participation, and current exercise behavior) among university students [5]. Teenage girls (12–18 years old; 71% African -American, 29% White) were View at Scopus; E. Pedhazur, Multiple Regression in Behavioral Research, Harcourt Brace, Orlando, Fla, USA, 1997. What not to do in multiple regression. Reliability of self-report measures of drug use in prevention research: Evaluation of the project SMART questionnaire via the test-retest reliability matrix. Research has identified a child behavior checklist (CBCL) profile for children with high levels of comorbid behavior problems, the dysregulation profile (DP), as another risk factor for drug use. Making it count : the improvement of social research and theory. Most research on organizations has used single individual perceptions to analyze their results through variants of a multiple regression model. Cattell-Horn-Carroll broad cognitive ability profiles of low math achievers. At the preliminary stage of the study, the principal investigator trained the research assistants for one week by lectures and practical demonstrations in the technique of interview. The data was screened in order to detect missing values and outliers as well as to test for conformity with the assumptions of multiple regression (normality, linearity, and homoscedasticity).