CODEWITHSUNDEEP
rsummarylmer
Nalerive
Nalerive

Reputation: 113

Colnames error after running Summary() in mixed model

R version 3.1.0 (2014-04-10)
lmer package version 1.1-6
lmerTest package version 2.0-6

I am currently working with lmer and lmerTest for my analysis. Every time I add an effect to the random structure, I get the following error when running summary():

#Fitting a mixed model: 
TRT5ToVerb.lmer3 = lmer(TRT5ToVerb ~ Group + Condition + (1+Condition|Participant) + (1|Trial), data=AllData, REML=FALSE, na.action=na.omit)
summary(TRT5ToVerb.lmer3)
 Error in `colnames<-`(`*tmp*`, value = c("Estimate", "Std. Error", "df",  : length of 'dimnames' [2] not equal to array extent

If I leave the structure like this: 

TRT5ToVerb.lmer2 = lmer(TRT5ToVerb ~ Group + Condition + (1|Participant) + (1|Trial),  data=AllData, REML=FALSE, na.action=na.omit)

there is no error run summary(TRT5ToVerb.lmer2), returning AIC, BIC, logLik deviance, estimates of the random effects, estimates of the fixed effects and their corresponding p-values, etc., etc.

So, apparently something happens when I run lmerTest, despite the fact that the object TRT5ToVerb.lmer3 is there. The only difference between both is the random structure: (1+Condition|Participant) vs. (1|Participant)

Some characteristics of my data:

  1. Both Condition and Group are categorical variables: Condition comprises 3 levels, and Group 2
  2. The dependent variable (TRT5ToVerb) is continuous: it corresponds to reading time in terms of ms
  3. This a repeated measures experiment, with 48 observations per participant (participants=28)

I read this threat, but I cannot see a clear solution. Will it be that I have to transform my dataframe to long format? And if so, then how do I work with that in lmer? I hope it is not that.

Thanks!

Disclaimer: I am neither an expert in R, nor in statistics, so please, have some patience.

Upvotes: 0

Views: 513

Answers (1)

Ben Bolker
Ben Bolker

Reputation: 226637

(Should be a comment, but too long/code formatting etc.)

This fake example seems to work fine with lmerTest 2.0-6 and a development version of lme4 (1.1-8; but I wouldn't expect there to be any relevant differences from 1.1-6 for this example ...)

AllData <- expand.grid(Condition=factor(1:3),Group=factor(1:2),
                  Participant=1:28,Trial=1:8)
form <- TRT5ToVerb ~ Group + Condition + (1+Condition|Participant) + (1|Trial)
library(lme4)
set.seed(101)
AllData$TRT5ToVerb <- simulate(form[-2],
               newdata=AllData,
               family=gaussian,
               newparam=list(theta=rep(1,7),sigma=1,beta=rep(0,4)))[[1]]
library(lmerTest)
lmer3 <- lmer(form,data=AllData,REML=FALSE)
summary(lmer3)

Produces:

Linear mixed model fit by maximum likelihood  ['merModLmerTest']
Formula: TRT5ToVerb ~ Group + Condition + (1 + Condition | Participant) +  
    (1 | Trial)
   Data: AllData

     AIC      BIC   logLik deviance df.resid 
  4073.6   4136.0  -2024.8   4049.6     1332 

Scaled residuals: 
     Min       1Q   Median       3Q      Max 
-2.97773 -0.65923  0.02319  0.66454  2.98854 

Random effects:
 Groups      Name        Variance Std.Dev. Corr     
 Participant (Intercept) 0.8546   0.9245            
             Condition2  1.3596   1.1660   0.58     
             Condition3  3.3558   1.8319   0.44 0.82
 Trial       (Intercept) 0.9978   0.9989            
 Residual                0.9662   0.9829            
Number of obs: 1344, groups:  Participant, 28; Trial, 8

Fixed effects:
              Estimate Std. Error         df t value Pr(>|t|)
(Intercept)    0.49867    0.39764   12.40000   1.254    0.233
Group2         0.03002    0.05362 1252.90000   0.560    0.576
Condition2    -0.03777    0.22994   28.00000  -0.164    0.871
Condition3    -0.27796    0.35237   28.00000  -0.789    0.437

Correlation of Fixed Effects:
           (Intr) Group2 Cndtn2
Group2     -0.067              
Condition2  0.220  0.000       
Condition3  0.172  0.000  0.794

Upvotes: 0

Related Questions