Analysis of Covariance in spss
Analysis of Covariance in spss
When you think of ANCOVA, you should think of sequential regression, as it can be conducted as such
Covariate(s) enter in step 1, categorical predictor after
Want to assess how much variance is accounted for in the DV after controlling for (partialing out) the effects of one or more continuous IV-covariates
ANCOVA always has at least 1 or more categorical, grouping IVs, and 1 or more continuous covariates).
Covariate:
Want high correlation with DV; low with other covariates
Want few covariates
Recall that you are partialling out variance in the DV, having the group variable explain very little leftover variance is unappealing
If covariate correlates with IV
Covariate(s) enter in step 1, categorical predictor after
Want to assess how much variance is accounted for in the DV after controlling for (partialing out) the effects of one or more continuous IV-covariates
ANCOVA always has at least 1 or more categorical, grouping IVs, and 1 or more continuous covariates).
Covariate:
Want high correlation with DV; low with other covariates
Want few covariates
Recall that you are partialling out variance in the DV, having the group variable explain very little leftover variance is unappealing
If covariate correlates with IV
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