[R-sig-ME] PredictSE.mer error message

yuki fujita yuki_himawari at hotmail.com
Thu Aug 14 00:13:49 CEST 2014


Hi

I am running glmer model with binomial distribution and want to get confidence interval using fixed effect for each treatments. 
However I get the error message I don't really understand therefore I don't know how to modify the code. 

My model is 

model_2b <- glmer(cbind(NumberCorrect,10-NumberCorrect)~ ADHDYN + EmotionType + (1 | ID),
                  family="binomial",data = data)

and here is the summary output

Generalized linear mixed model fit by maximum likelihood (Laplace Approximation) ['glmerMod']
 Family: binomial  ( logit )
Formula: cbind(NumberCorrect, 10 - NumberCorrect) ~ ADHDYN + EmotionType +      (1 | ID)
   Data: data

     AIC      BIC   logLik deviance df.resid 
  2000.5   2034.5   -992.3   1984.5      508 

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-3.4809 -0.7256  0.1760  0.7238  3.4354 

Random effects:
 Groups Name        Variance Std.Dev.
 ID     (Intercept) 0.1337   0.3656  
Number of obs: 516, groups:  ID, 86

Fixed effects:
             Estimate Std. Error z value Pr(>|z|)    
(Intercept)   1.15637    0.10193  11.345  < 2e-16 ***
ADHDYNYES    -0.27728    0.10236  -2.709  0.00675 ** 
EmotionType2  2.04670    0.17845  11.469  < 2e-16 ***
EmotionType3 -0.24761    0.10744  -2.305  0.02119 *  
EmotionType4 -1.79462    0.10811 -16.600  < 2e-16 ***
EmotionType5 -0.04793    0.10939  -0.438  0.66129    
EmotionType6 -1.01871    0.10445  -9.753  < 2e-16 ***
---

And I used the code below to get CI's but got error message.

> predictSE.mer(model_2b, NEWdata,se.fit=TRUE, type="response",level=0, print.matrix=FALSE)
Error in predictSE.mer(model_2b, NEWdata, se.fit = TRUE, type = "response",  : 
  no slot of name "offset" for this object of class "glmerMod"
Can you please guide me where I am getting wrong? I noted the sd of random effect is quite large- so might be worth to do the simulation. I heard about MCMCsamp but is this the way to go?

Thank you kindly
Yuki


 		 	   		  
	[[alternative HTML version deleted]]



More information about the R-sig-mixed-models mailing list