Dear R users, I'm pretty new on using lmer package. My response is binary and I have fixed treatment effect (2 treatments) and random center effect (7 centers). I want to test the effect of treatment by fitting 2 models:
Model 1: center effect (random) only Model 2: trt (fixed) + center (random) + trt*center interaction. Then, I want to compare these 2 models with Likelihood Ratio Test. Here are my lmer codes that I don't feel comfortable about their correctness. model1 <- try(lmer(cbind( yvect, nvect-yvect) ~ 1 + (1 | center), family = binomial, niter = 25, method = "Laplace", control = list(usePQL = FALSE) )) model2 <- try(lmer(cbind( yvect, nvect-yvect) ~ trt*center + ( 1 | center) , family = binomial, niter = 25, method = "Laplace", control = list(usePQL = FALSE) )) (I have attached outputs below) What I don't understand is; I thought in model2 I have defined center effect as a random effect. Then how come I got center effects and trt*center interactions under the fixed effects list on the output? Probably I didn't understand how to set up these models in lmer. Could anyone help me about this? Thanks a lot for your help... Emine model1 <- try(lmer(cbind( yvect, nvect-yvect) ~ 1 + (1 | center), family = binomial, niter = 25, method = "Laplace", control = list(usePQL = FALSE) )) >summary(model1) Generalized linear mixed model fit using Laplace Formula: cbind(yvect, nvect - yvect) ~ 1 + (1 | center) Family: binomial(logit link) AIC BIC logLik deviance 236.817 238.0951 -116.4085 232.817 Random effects: Groups Name Variance Std.Dev. center (Intercept) 0.088127 0.29686 number of obs: 14, groups: center, 7 Estimated scale (compare to 1) 0.2672612 Fixed effects: Estimate Std. Error z value Pr(>|z|) (Intercept) -0.32084 0.14709 -2.1812 0.02917 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 ################## model2 <- try(lmer(cbind( yvect, nvect-yvect) ~ trt*center + ( 1 | center) , family = binomial, niter = 25, method = "Laplace", control = list(usePQL = FALSE) )) >summary(model2) Generalized linear mixed model fit using Laplace Formula: cbind(yvect, nvect - yvect) ~ trt * center + (1 | center) Family: binomial(logit link) AIC BIC logLik deviance 30 39.58586 -1.547024e-07 3.094048e-07 Random effects: Groups Name Variance Std.Dev. center (Intercept) 5e-10 2.2361e-05 number of obs: 14, groups: center, 7 Estimated scale (compare to 1) 0.2672612 Fixed effects: Estimate Std. Error z value Pr(>|z|) (Intercept) -1.060869 0.065372 -16.2282 < 2e-16 *** trt2 1.118029 0.086842 12.8743 < 2e-16 *** center2 -0.325428 0.504256 -0.6454 0.51869 center3 -0.325440 0.504258 -0.6454 0.51868 center4 0.655407 0.413449 1.5852 0.11292 center5 -0.325433 0.504256 -0.6454 0.51869 center6 -0.325421 0.504255 -0.6454 0.51870 center7 0.655422 0.413448 1.5853 0.11291 trt2:center2 0.673737 0.651313 1.0344 0.30094 trt2:center3 -0.137183 0.651314 -0.2106 0.83318 trt2:center4 -0.307083 0.583845 -0.5260 0.59891 trt2:center5 -0.137203 0.651314 -0.2107 0.83316 trt2:center6 1.654555 0.712419 2.3224 0.02021 * trt2:center7 0.673705 0.651311 1.0344 0.30096 --- _________________________________________________________________ Office Live http://clk.atdmt.com/MRT/go/aub0540003042mrt/direct/01/ ______________________________________________ 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 and provide commented, minimal, self-contained, reproducible code.