I have a
glmer model from the R package
lme4 with a binomial distribution and I was wondering whether I am interpreting the model output correctly.
In my model I have a response variable correctness (incorrect, correct) -> so (0, 1).
Predictors are: condition (0, 1) and treatment (0, 1).
My model looks like this:
model<- glmer(correct~ treatment + condition + treatment :condition + (1|id) + (1|item), family= binomial)
My model output:
summary(model) Fixed effects: Estimate Std. Error z value Pr(>|z|) (Intercept) 2.94373 0.23510 12.521 < 2e-16 *** treatment1 0.09146 0.31465 0.291 0.771 cond1 -0.95974 0.23691 -4.051 5.1e-05 *** cond1:treatment1 -0.13183 0.32034 -0.412 0.681
My interpretation is:
cond1 : The chance of answering correctly decreases significantly by -0.95974 when comparing condition 0 to condition 1 (p < .001).
cond1:treatment1: When comparing condition 0 to condition 1 the decrease of chance by -0.13183 of answering correctly decreases not signficantly more for the treatment group as for the non treatment group (p = .681).
Is my interpretation correct? Also, would you report more than p values and estimates?
Thanks in advance!