Dear all,
when performing a meta analysis I have two results obtained with logLik
and lme, which I do not quite understand.
The results are based on these data:
study or var
1 0.10436 0.299111
2 -0.03046 0.121392
3 0.76547 0.319547
4 -0.19845 0.025400
5 -0.10536 0.025041
6 -0.11653 0.040469
7 0.09531 0.026399
8 0.26236 0.017918
9 -0.26136 0.020901
10 0.45742 0.035877
11 -0.59784 0.076356
12 -0.35667 0.186879
13 -0.10536 0.089935
14 -0.31471 0.013772
15 -0.10536 0.089935
16 0.02956 0.004738
17 0.60977 0.035781
18 -0.30111 0.036069
19 0.01980 0.024611
20 0.00000 0.002890
21 -0.04082 0.015863
22 0.02956 0.067069
23 0.18232 0.010677
24 0.26236 0.017918
25 0.32208 0.073896
26 0.67803 0.489415
27 -0.96758 0.194768
28 0.91629 0.051846
29 0.32208 0.110179
30 -1.13943 0.086173
31 -0.47804 0.103522
32 0.16551 0.004152
33 0.46373 0.023150
34 -0.52763 0.050384
35 0.10436 0.003407
36 0.55389 0.054740
The first result concerns logLik
m0<-glm(or~1,family=gaussian(),data=temp,weights=1./var)
logLik(m0)
`log Lik.' -7.10697 (df=2)
For comparison direct calculation of the log likelihood gives:
ll<-sum(log(dnorm(temp$or,fitted(m0),sqrt(temp$var))))
> ll
[1] -33.19137
Does logLik omit constants or how can this discrepancy be explained?
My second problem is with lme. I want to use FIXED variances in the
estimation process:
m.lm1<-lme(or~1,random=~1|study,weights=varFixed(~var),data=temp,method="ML")
> m.lm1
Linear mixed-effects model fit by maximum likelihood
Data: temp
Log-likelihood: -14.22718
Fixed: or ~ 1
(Intercept)
0.05597874
Random effects:
Formula: ~1 | study
(Intercept) Residual
StdDev: 0.002656846 1.795564
Variance function:
Structure: fixed weights
Formula: ~var
Number of Observations: 36
Number of Groups: 36
This is very much the fixed effects result and quite different from the
result I obtain with SAS. Are there any tips to correct this result?
Many thanks in advance
Peter
______________________________________________
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
