scoyoc
2014-Dec-15 17:08 UTC
[R] How do I interpret linear mixed model contrast estimates from multcomp::glht()?
?? How do the rows in the summary (e.g. "1 == 0") correspond to the model? The answer is buried *contrast::contrast()*, but I can't figure it out. Consider this modified example I stole from here <https://stat.ethz.ch/pipermail/r-sig-mixed-models/2009q4/003061.html>...> options(contrasts = c(factor = "contr.SAS", ordered = "contr.poly")) > library("mlmRev") > library("lme4") > library("lmerTest") > library("contrast") > library("multcomp") > > data("egsingle") > # Linear mixed model > math.lmm <- lmer(math ~ year * size + female + (1|childid) +(1|schoolid), egsingle)> # Linear model > math.lm <- lm(math ~ year * size + female, data = egsingle) > # Calculate contrast matrix > cc<-contrast(math.lm, a = list(year = c(0.5, 1.5, 2.5), size = 380,female = levels(egsingle$female)), + b = list(year = c(0.5, 1.5, 2.5), size = 800, female = levels(egsingle$female)))> # Calculate estimates > summary(glht(math.lmm, linfct = cc$X))Simultaneous Tests for General Linear Hypotheses Fit: lme4::lmer(formula = math ~ year * size + female + (1 | childid) + (1 | schoolid), data = egsingle) Linear Hypotheses: Estimate Std. Error z value Pr(>|z|) 1 == 0 0.12774 0.08020 1.593 0.1272 2 == 0 0.15322 0.08066 1.900 0.0669 . 3 == 0 0.17870 0.08178 2.185 0.0341 * 4 == 0 0.12774 0.08020 1.593 0.1273 5 == 0 0.15322 0.08066 1.900 0.0669 . 6 == 0 0.17870 0.08178 2.185 0.0342 * --- Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 (Adjusted p values reported -- single-step method) The row names correspond to the levels of *year* and *female,* and are probably Female:0.5, Female:1.5, Female:2.5, and so on. But how do I pull that out of the contrast() object *cc?* It might be simple with 3 fixed effects, but my current project has 5 fixed effects, four 2-way interactions, and one 3-way interaction, and the summary table has 24 rows. Ultimately I would like to create a dataframe so I can plot the contrasts, something like this...> x = summary(glht(math.lmm, linfct = cc$X)) > # Contrast data frame > math.contr = data.frame(Effect.Interaction = reference_something_in_cc,Estimate x[["test"]]$coefficients, Std.Error = x[["test"]]$sigma) Thanks for the help! Cheers, MVS ====Matthew Van Scoyoc <mvanscoyoc at aggiemail.usu.edu>https://sites.google.com/site/scoyoc/ ====Think SNOW! ----- MVS ====Matthew Van Scoyoc Graduate Research Assistant, Ecology Wildland Resources Department & Ecology Center Quinney College of Natural Resources Utah State University Logan, UT ====Think SNOW! -- View this message in context: http://r.789695.n4.nabble.com/How-do-I-interpret-linear-mixed-model-contrast-estimates-from-multcomp-glht-tp4700797.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]]