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visualizing effects of fixed factors and partial/whole model statistics
2 messages · Timothy Farkas, John Fox
Dear Tim, You might take a look at the effects package, which handles objects produced by lmer(), and generalizes the idea of (the horribly named) "least-squares means." The functions to use directly are allEffects(), effect(), and Effect() -- see ?effect. I hope this helps, John ----------------------------------------------- John Fox Senator McMaster Professor of Social Statistics Department of Sociology McMaster University Hamilton, Ontario, Canada
-----Original Message----- From: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed- models-bounces at r-project.org] On Behalf Of Timothy Farkas Sent: Sunday, October 07, 2012 10:13 AM To: r-sig-mixed-models at r-project.org Subject: [R-sig-ME] visualizing effects of fixed factors and partial/whole model statistics Hi All, I have two related practical questions concerning GLMMs. I hope my questions aren't too simplistic for this list, but other forums have been not been responsive. My model is specified as follows: lmer(countData ~ 3LevelFactor + continuous + (1|5LevelFactor), family=poisson) and there is some redundancy between the fixed components and between the continuous variable and random factor, but not loads. 1) How can I visualize the effect of the fixed factor while accounting for the continuous variable and random factor? I'm looking to make a column graph with standard error bars that would be the multiple-regression equivalent of a partial plot. I think some people would refer to this as a "least-squared means" plot? Ideally, I could obtain a vector of adjusted values for the dependent variable and plot them over levels of the factor. Because redundancy is low, I'm OK with plotting raw data, but on principle I like my visualizations to accurately reflect my analysis if possible. 2) Are there statistics like the R-sq of linear regression that will denote how much variation in my dependent variable is explained by my model? What about statistics like partial-R-sq, that denote the amount of variation explained by individual fixed parameters? Cheers, tim -- Timothy E. Farkas Dept. Animal and Plant Sciences Alfred Denny Building University of Sheffield Western Bank Sheffield S10 2TN United Kingdom [[alternative HTML version deleted]]
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