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| = When should I use a logit analysis as opposed to an arcsine transformed ANOVA? = Jaeger (2008) advocates and illustrates using a logistic regression approach when the proportions are near 0 and 1 over the traditional method of an arcsine transform in an ANOVA. The latter can give spuriously statistically significant results in these cases. He suggests using separate logistic regressions for each subject and item (Lorch and Myers, 1990) and also use of the [:FAQ/mixedR: lmer procedure in the freeware R] for fitting random effects to binomial data using generalized linear mixed models. The mixed refers to allowing the fitting of both fixed and random factors. The logistic regression he says has the advantage of giving directional comparisons via its regression coefficients (Odds Ratios) whereas post-hoc contrasts are needed to obtain this information using the ANOVA approach. __References__ [attachment:Jaeger.pdf Jaeger TF (2008). Categorical Data Analysis: Away from ANOVAs (transformation or not) and towards Logit Mixed Models.] ''J. Mem Lang'' '''59(4)''' 434-446. Lorch RF and Myers JL (1990). Regression analyses of repeated measures data in cognitive research. ''Journal of Experimental Psychology: Learning, Memory and Cognition'' '''16(1)''' 149-157. |
VHuZOi , [url=http://tfohfpqoxnll.com/]tfohfpqoxnll[/url], [link=http://tzdrtmszrlfv.com/]tzdrtmszrlfv[/link], http://psoolykjibsa.com/ ---- CategoryHomepage |
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None: FAQ/Jaeger (last edited 2022-01-31 09:29:07 by PeterWatson)