[R] extracting coefficients from lmer
Jonathan Williams
jonathan.williams at pharmacology.oxford.ac.uk
Tue Jan 10 11:54:34 CET 2006
Dear R-Helpers,
I want to compare the results of outputs from glmmPQL and lmer analyses.
I could do this if I could extract the coefficients and standard errors
from the summaries of the lmer models. This is easy to do for the glmmPQL
summaries, using
> glmm.fit <- try(glmmPQL(score ~ x*type, random = ~ 1 | subject, data = df,
family = binomial), TRUE)
> summary(glmmPQL.fit)$tTable
Linear mixed-effects model fit by maximum likelihood
Data: df
AIC BIC logLik
1800.477 1840.391 -890.2384
Random effects:
Formula: ~1 | subject
(Intercept) Residual
StdDev: 0.6355517 0.9650671
Variance function:
Structure: fixed weights
Formula: ~invwt
Fixed effects: score ~ x * type
Value Std.Error DF t-value p-value
(Intercept) -0.0812834 0.2933314 294 -0.2771043 0.7819
x1 0.4143072 0.4180624 98 0.9910176 0.3241
type2 0.8509166 0.4084443 294 2.0833112 0.0381
type3 0.6691275 0.4024369 294 1.6626894 0.0974
type4 -0.7830413 0.4123851 294 -1.8988109 0.0586
x1:type2 1.0643239 0.6791126 294 1.5672274 0.1181
x1:type3 -0.7533085 0.5674532 294 -1.3275253 0.1854
x1:type4 -0.0549616 0.5777216 294 -0.0951351 0.9243
etc.
However, there seems to be no route to extract the corresponding information
from the lmer model:-
> lmer.fit=try(lmer(score~x*type+(1|subject), data=df, family=binomial,
method='AGQ'),TRUE)
> summary(lmer.fit)
Generalized linear mixed model fit using AGQ
Formula: score ~ x * type + (1 | subject)
Data: df
Family: binomial(logit link)
AIC BIC logLik deviance
510.2616 550.1762 -245.1308 490.2616
Random effects:
Groups Name Variance Std.Dev.
subject (Intercept) 0.46269 0.68021
# of obs: 400, groups: subject, 100
Estimated scale (compare to 1) 1.019134
Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -0.087284 0.300896 -0.29008 0.77175
x1 0.446289 0.428844 1.04068 0.29803
type2 0.913571 0.418978 2.18047 0.02922 *
type3 0.719023 0.412816 1.74175 0.08155 .
type4 -0.839842 0.423021 -1.98534 0.04711 *
x1:type2 1.112673 0.696629 1.59722 0.11022
x1:type3 -0.809599 0.582089 -1.39085 0.16427
x1:type4 -0.062235 0.592623 -0.10502 0.91636
etc.
> summary(lmer.fit)$tTable
NULL
> names(summary(lmer.fit))
NULL
> names(lmer.fit)
NULL
> lmer.fit$coef
NULL
So, then I tried to find out if lmer returns different information.
> help(lmer)
This says "see lmer-class" ->
> help(lmer-class)
No documentation for 'lmer - class' in specified packages and libraries:
you could try 'help.search("lmer - class")'
So, then I tried
> help.search('lmer-class')
This returns
Help files with alias or concept or title matching 'lmer-class' using fuzzy
matching:
lmer-class(Matrix) Mixed model representations
So, I loaded library Matrix and tried again
> library(Matrix)
> help(lmer-class)
No documentation for 'lmer - class' in specified packages and libraries:
you could try 'help.search("lmer - class")'
If someone could tell me how to extract the Estimates and Std. Errors from
the lmer summary, I'd be very grateful. I would also be very grateful if
someone
could let me know why the Estimates and Std. Errors from the lmer model are
both
larger than those from the glmmPQL model.
I am running R 2.2.1 on a Windows XP machine.
Thanks,
Jonathan Williams
More information about the R-help
mailing list