Patrick Dattalo
- Published in print:
- 2013
- Published Online:
- May 2013
- ISBN:
- 9780199773596
- eISBN:
- 9780199332564
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199773596.001.0001
- Subject:
- Social Work, Research and Evaluation
Multivariate procedures allow social workers and other human services researchers to analyze complex, multidimensional social problems and interventions in ways that minimize oversimplification. This ...
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Multivariate procedures allow social workers and other human services researchers to analyze complex, multidimensional social problems and interventions in ways that minimize oversimplification. This book provides an introduction to four procedures for the analysis of multiple dependent variables: multivariate analysis of variance (MANOVA), multivariate analysis of covariance (MANCOVA), multivariate multiple regression (MMR), and structural equation modeling (SEM). Each procedure is presented in a way that allows readers to compare and contrast them in terms of appropriate research context; required statistical assumptions, including levels of measurement of variables to be modeled; analytical steps; sample size; and strengths and weaknesses. This book facilitates course extensibility in scope and depth by allowing instructors to supplement course content with rigorous statistical procedures. The book provides detailed annotated examples using Stata, SPSS (PASW), SAS, and Amos.Less
Multivariate procedures allow social workers and other human services researchers to analyze complex, multidimensional social problems and interventions in ways that minimize oversimplification. This book provides an introduction to four procedures for the analysis of multiple dependent variables: multivariate analysis of variance (MANOVA), multivariate analysis of covariance (MANCOVA), multivariate multiple regression (MMR), and structural equation modeling (SEM). Each procedure is presented in a way that allows readers to compare and contrast them in terms of appropriate research context; required statistical assumptions, including levels of measurement of variables to be modeled; analytical steps; sample size; and strengths and weaknesses. This book facilitates course extensibility in scope and depth by allowing instructors to supplement course content with rigorous statistical procedures. The book provides detailed annotated examples using Stata, SPSS (PASW), SAS, and Amos.
