By Albert R. Wildt
This publication provides a strategy for studying the consequences 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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Extra resources for Analysis of Covariance (Quantitative Applications in the Social Sciences)
Analysis of covariance may be used with each of these perspectives. The first perspective, which we designate as the experimental perspective, involves those instances when interest centers on the differences occurring in the dependent variable over the categories, or levels of the qualitative independent variable(s). In these cases it is assumed that one or more quantitative independent variables, referred to as covariates, influence the dependent variable in a linear fashion, and independently of the level or category of the qualitative independent variable(s); but this relationship is not of primary concern to the researcher (the covariate is considered a nuisance variable).
The reason is that in cases where group effects exist the use of this second method would result in a covariance adjustment which would also remove a portion of the variation attributable to the treatment or group effect. This would be unsatisfactory, and therefore, the approach given by equation 11 is used. , ti = 0 for all i, can be tested. As in analysis of variance, an F-statistic is computed. It is of the form, Under the null hypothesis (and the model assumptions) this ratio has an F-distribution with degrees of freedom k-1 and N-k-1.
Case 2 involves quantitative independent variables. In this context the researcher is usually investigating for possible changes in the dependent variable which may accompany changes in the independent variable(s). Correlation and regression analysis are appropriate procedures here. Case 3 involves both quantitative and qualitative independent variables. This case is of primary Page 8 concern for the present discussion, and two alternate (though statistically similar) procedures are available for analyzing situations which meet this condition.