Hello R users I'm using MuMIn but for some reason I'm not getting the adjusted confidence interval and uncoditional SE whe I use model.avg().
I took into consideration the steps provided by Grueber et al (2011) Multimodel inference in ecology and evolution: challenges and solutions in JEB. I created a global model to see if malaria prevalence (binomial distribution) is related to any life history traits of 14 different birds species, while controling for Family and genus in a GLMM: global.model.Para<-lmer(cbind(Parahaemoproteus,FailPh)~factor(SS)+factor(NT)+NH+W+IT+factor(MS)+(1|Family/Genus),family=binomial,data=malaria) I than standardize the input variables using the function standardize form the arm package: stdz.model.Para<-standardize(global.model.Para,standardize.y=FALSE) But I get this message: Warning messages lost: In is.na(thedata): is.na() aplied to an object different from list or vector of type "Null" summary(stdz.model.Para) Generalized linear mixed model fit by the Laplace approximation Formula: cbind(Parahaemoproteus, FailPh) ~ factor(SS) + factor(NT) + z.NH + z.W + z.IT + factor(MS) + (1 | Family/Genus) Data: malaria AIC BIC logLik deviance 45.89 51.64 -13.95 27.89 Random effects: Groups Name Variance Std.Dev. Genus:Family (Intercept) 1.4262 1.1942 Family (Intercept) 0.0000 0.0000 Number of obs: 14, groups: Genus:Family, 12; Family, 5 Fixed effects: Estimate Std. Error z value Pr(>|z|) (Intercept) -4.6494 1.1791 -3.943 8.04e-05 *** factor(SS)1 3.7793 2.0709 1.825 0.068 . factor(NT)1 1.8975 1.2793 1.483 0.138 z.NH 0.4902 2.1099 0.232 0.816 z.W -1.6237 1.5957 -1.018 0.309 z.IT -0.7656 1.9598 -0.391 0.696 factor(MS)1 -2.0603 1.3907 -1.481 0.138 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Correlation of Fixed Effects: (Intr) f(SS)1 f(NT)1 z.NH z.W z.IT factor(SS)1 -0.202 factor(NT)1 -0.599 0.090 z.NH 0.058 -0.790 -0.178 z.W 0.232 -0.632 0.039 0.503 z.IT 0.051 0.569 0.323 -0.851 -0.339 factor(MS)1 -0.176 -0.632 -0.319 0.538 0.165 -0.567 I then proceed to use the dredge fucntion: model.set.Para<-dredge(stdz.model.Para) model.set.Para Global model: glmer(formula = cbind(Parahaemoproteus, FailPh) ~ factor(SS) + factor(NT) + z.NH + z.W + z.IT + factor(MS) + (1 | Family/Genus), data = malaria, family = "binomial") --- Model selection table (Int) fct(MS) fct(NT) fct(SS) z.I z.N z.W k Dev. AIC AICc delta weight 4 -5.231 + 4 34.64 42.64 47.08 0.0000 0.290 9 -4.750 + + 5 30.00 40.00 47.50 0.4142 0.236 . . . Random terms: 1 | Family/Genus I then select the models with delta value up to 7: top.models.Para<-get.models(model.set.Para,subset=delta<=7) top.models But when I do the model average I do not seem to be getting the variance or Uncoditional SE and I'm guessing that the Confidence interval are no conditional either: model.avg(top.models.Para,method="NA") Model summary: Deviance AICc Delta Weight 3 34.64 47.08 0.00 0.30 1+3 30.00 47.50 0.41 0.25 4+5 31.49 48.99 1.90 0.12 3+5 32.29 49.79 2.70 0.08 3+6 33.02 50.52 3.44 0.05 5 38.41 50.86 3.77 0.05 3+4 33.77 51.27 4.19 0.04 1+3+5 27.85 51.85 4.77 0.03 3+4+5 27.86 51.86 4.78 0.03 1+3+4 28.58 52.58 5.49 0.02 1+5 35.33 52.83 5.75 0.02 1+3+6 29.34 53.34 6.26 0.01 1+2+3 30.02 54.02 6.93 0.01 Variables: 1 2 3 4 5 6 factor(MS) factor(NT) factor(SS) z.IT z.NH z.W Averaged model parameters: Coefficient SE Lower CI Upper CI (Intercept) -4.75 1.410 -7.510 -1.9900 factor(MS)1 -1.54 0.809 -3.120 0.0471 factor(NT)1 2.28 1.310 -0.286 4.8500 factor(SS)1 3.30 0.968 1.400 5.2000 z.IT -2.79 2.230 -7.160 1.5800 z.NH 2.28 1.660 -0.968 5.5300 z.W -1.74 1.490 -4.650 1.1800 Confidence intervals are unadjusted Relative variable importance: factor(SS) factor(MS) z.NH z.IT z.W factor(NT) 0.82 0.33 0.32 0.20 0.07 0.01 Does anyone know what I might be doing wrong? thanks for the help Marcos -- View this message in context: http://r.789695.n4.nabble.com/MuMIn-Problem-getting-adjusted-Confidence-intervals-tp3776500p3776500.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.