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Published byMitchell Cummings Modified over 9 years ago
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Analysis of covariance
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When… ANCOVA is an ‘extra’ on an ANOVA ANOVA outcome = number of words learned IV = Sex ANCOVA adds a covariate covariate = size of first language vocabulary
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Control Variables that influence the outcome Manipulate Control hold steady randomise enter into the statistical model
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Control Hold steady Everyone has same L1 vocab Mean of groups is same for L1 vocab Randomise sometimes you can’t (e.g. Sex) ANCOVA – record L1 vocab and allow statistically
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ANCOVA in SPSS Use GLM / Univariate Enter outcome as dependent variable Enter Sex as ‘Fixed’ IV Enter L1 vocab as ‘covariate’
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ANCOVA assumptions Linearity relation between covariate and outcome is (roughly) linear ‘Homogeneity of regression ’ relation between covariate and outcome is the same for both Men and Women [relation is the same at each level of the IV]
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Checking Homogeneity of regression in SPSS A second ‘run’ through Analyse/GLM/univariate Click the ‘model’ button’ Select IV (Sex) and Covariate and ‘click across’; Now select both together and ‘click across’; Continue as before…. Interaction effect – must not be significant
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MANOVA Multiple dependent variables ‘converted’ into one composite DV Assumptions – see Pallant SPSS Survival Guide (similar to Multiple Regression: Linearity, Mahalanobis distances) Plus homescedasticity (use Box’s M with a conservative p-value) Further reading: Tabachnik & Fidell
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