[R] lmer binomial model overestimating data?

Martin Henry H. Stevens hstevens at muohio.edu
Wed Jun 14 14:38:29 CEST 2006

```Hi folks,
Warning: I don't know if the result I am getting makes sense, so this
may be a statistics question.

The fitted values from my binomial lmer mixed model seem to
consistently overestimate the cell means, and I don't know why. I
assume I am doing something stupid.

Below I include code, and a binary image of the data is available at
http://www.cas.muohio.edu/~stevenmh/tf.RdataBin

This was done with `Matrix' version 0.995-10 and `lme4' version
0.995-2. and R v. 2.3.1 on a Mac, OS 10.4.6.

The binomial model below ("mod") was reduced from a more complex one
by first using AIC, BIC and LRT for "random" effects, and then
relying on Helmert contrasts and AIC, BIC, and LRT to simplify fixed
effects. Maybe this was wrong?

> library(lme4)

> options(contrasts=c("contr.helmert", "contr.poly"))
> mod <- lmer(tfb ~ reg+nutrient+amd +reg:nutrient+
+     (1|rack) + (1|popu) +  (1|gen), data=dat.tb2, family=binomial,
method="Laplace")
> summary(mod)
Generalized linear mixed model fit using Laplace
Formula: tfb ~ reg + nutrient + amd + reg:nutrient + (1 | rack) + (1
|      popu) + (1 | gen)
Data: dat.tb2
AIC    BIC  logLik deviance
402.53 446.64 -191.26   382.53
Random effects:
Groups Name        Variance Std.Dev.
gen    (Intercept) 0.385    0.621
popu   (Intercept) 0.548    0.741
rack   (Intercept) 0.401    0.633
number of obs: 609, groups: gen, 24; popu, 9; rack, 2

Estimated scale (compare to 1)  0.80656

Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept)       2.391      0.574    4.17  3.1e-05
reg1              0.842      0.452    1.86  0.06252
reg2              0.800      0.241    3.32  0.00091
nutrient1         0.788      0.197    4.00  6.3e-05
amd1             -0.540      0.139   -3.88  0.00010
reg1:nutrient1    0.500      0.227    2.21  0.02734
reg2:nutrient1   -0.176      0.146   -1.21  0.22794

Correlation of Fixed Effects:
(Intr) reg1   reg2   ntrnt1 amd1   rg1:n1
reg1         0.169
reg2        -0.066 -0.191
nutrient1    0.178  0.231 -0.034
amd1        -0.074 -0.044 -0.052 -0.078
reg1:ntrnt1  0.157  0.307 -0.180  0.562 -0.002
reg2:ntrnt1 -0.028 -0.154  0.236  0.141  0.033 -0.378
> X <- mod @ X
> fitted <- X %*% fixef(mod)
>
> unlogitH <- function(x) {( 1 + exp(-x) )^-1}
> (result <- data.frame(Raw.Data=with(dat.tb2,
+                          tapply(tfb, list(reg:nutrient:amd),
+                          mean ) ),
+         Fitted.Estimates=with(dat.tb2,
+                          tapply(fitted, list(reg:nutrient:amd),
+                          function(x) unlogitH(mean(x))  ) )  ))
Raw.Data Fitted.Estimates
SW:1:unclipped  0.50877          0.69520
SW:1:clipped    0.41304          0.43669
SW:8:unclipped  0.67273          0.85231
SW:8:clipped    0.52830          0.66233
NL:1:unclipped  0.88889          0.81887
NL:1:clipped    0.53571          0.60578
NL:8:unclipped  0.96552          0.98830
NL:8:clipped    0.96154          0.96635
SP:1:unclipped  0.98649          0.98361
SP:1:clipped    0.92537          0.95328
SP:8:unclipped  1.00000          0.99308
SP:8:clipped    0.95890          0.97992
> ### Perhaps the cell SP:8:clipped = 1.0 is messing up the fit?
> pdf("RawAndFitted.pdf")
> par(mar=c(8,3,2,2), las=2)
> barplot(t(result), beside=TRUE )
> box(); title("Fractions of Plants Producing Fruits")
> legend("topleft", c("Raw Data", "Fitted Values"),
+        fill=gray.colors(2), bty="n" )
> dev.off()
quartz
2
>

_
platform       powerpc-apple-darwin8.6.0
arch           powerpc
os             darwin8.6.0
system         powerpc, darwin8.6.0
status
major          2
minor          3.1
year           2006
month          06
day            01
svn rev        38247
language       R
version.string Version 2.3.1 (2006-06-01)
>

Dr. M. Hank H. Stevens, Assistant Professor
338 Pearson Hall
Botany Department
Miami University
Oxford, OH 45056

Office: (513) 529-4206
Lab: (513) 529-4262
FAX: (513) 529-4243
http://www.cas.muohio.edu/~stevenmh/
http://www.muohio.edu/ecology/
http://www.muohio.edu/botany/
"E Pluribus Unum"

```