By Albert R. Wildt
This publication provides a method for interpreting the results of variables, teams, and coverings in either experimental and observational settings. It considers not just the most results of 1 variable upon one other, but in addition the consequences of crew situations.
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Additional resources for Analysis of Covariance (Quantitative Applications in the Social Sciences)
First, analysis of covariance provides a method to adjust for preexisting differences among the intact groups employed in the experiment. In this respect, analysis of covariance may remove bias attributable to the fact that the intact groups are not similar, or matched, on certain important test unit characteristics. Second, the use of analysis of covariance in these situations may result in the same benefit as in a completely randomized experiment, that is, increase the precision of the experiment by reducing the error variance.
A summary of the computational formulae associated with the analysis of covariance for the completely randomized design is presented in Table 1. The F-statistic given by equation 12 is only a summary measure which indicates if any significant group differences in the dependent variable exist. If significant differences are present, one naturally wants to investigate the nature of these differences. Therefore, when the F-ratio is significant it is customary to compute the group means adjusted for the covariate to aid in the interpretation of the results.
Ahtola, Olli. publisher : Sage Publications, Inc. isbn10 | asin : 0803911645 print isbn13 : 9780803911642 ebook isbn13 : 9780585216676 language : English subject Analysis of variance. 5/352 subject : Analysis of variance. Analysis of Covariance SAGE UNIVERSITY PAPERS Series: Quantitative Applications in the Social Sciences Series Editor: Michael S. Lewis-Beck, University of Iowa Editorial Consultants Richard A. Berk, Sociology, University of California, Los Angeles William D. Berry, Political Science, Florida State University Kenneth A.
Analysis of Covariance (Quantitative Applications in the Social Sciences) by Albert R. Wildt