[R] starting values for lmer fixed effects

[Richard Chandler]

Hi,

Is there a way to provide starting values for the fixed effects in
lmer()? I'd like to fit the following model, which requires starting
values in the glm.fit() part of the code:

lmer(dbh.sum ~ Treatment + (1|Site), nets, gaussian("log"),
	subset=Treatment!="sforest" & iocTreat!="forest")

I tried tinkering with the code but I couldn't figure out the
namespace problems I ran into. I also saw an earlier R-help post with
a reply mentioning a possible lmer-initialize function that I couldn't
find. I can fit the model without the random effect using glm:

Call:
glm(formula = dbh.sum ~ Treatment, family = gaussian("log"),
    data = nets, subset = Treatment != "sforest" & iocTreat !=
        "forest", start = c(5, 5, 5))

Deviance Residuals:
    Min       1Q   Median       3Q      Max
-270.55   -72.32   -36.25    40.92   793.02

Coefficients:
               Estimate Std. Error t value Pr(>|t|)
(Intercept)     5.87873    0.04536 129.603  < 2e-16 ***
Treatmentioc   -1.82540    0.40063  -4.556 9.83e-06 ***
Treatmentshade -0.88166    0.11856  -7.436 4.69e-12 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for gaussian family taken to be 18392.07)

    Null deviance: 5763318  on 174  degrees of freedom
Residual deviance: 3163431  on 172  degrees of freedom
AIC: 2220.0

Number of Fisher Scoring iterations: 10



Also, are there plans to create a predict function for lmer? Thanks.

Richard



-- 
Richard Chandler, PhD student
Department of Natural Resources Conservation
UMass Amherst
(413)545-1237