I have conducted a within-subject experiment. The DV of the experiment is a categorical variable (0 or 1) and the IV has three levels (1 = none, 2 = weak, 3 = strong) Since the DV is binary, I've built a logistic mixed-effects regression model. Here is the code I ran below:
model <- glmer(DV ~ IV + (1|subjects) + (1|items), data=df, family=binomial("logit"))
The model has been converged as below:
Generalized linear mixed model fit by maximum likelihood (Laplace Approximation) ['glmerMod'] Family: binomial ( logit ) Formula: DV ~ IV + (1 | subjects) + (1 | items) Data: df AIC BIC logLik deviance df.resid 1370.3 1398.4 -680.2 1360.3 2035 Scaled residuals: Min 1Q Median 3Q Max -9.0454 -0.2655 0.1214 0.2882 7.7130 Random effects: Groups Name Variance Std.Dev. items (Intercept) 1.9754 1.4055 subjects (Intercept) 0.4548 0.6744 Number of obs: 2040, groups: items, 60; subjects, 34 Fixed effects: Estimate Std. Error z value Pr(>|z|) (Intercept) -3.1913 0.3899 -8.185 0.000000000000000272 *** type.strong 6.1598 0.5401 11.405 < 0.0000000000000002 *** type.weak 4.2876 0.5046 8.498 < 0.0000000000000002 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Correlation of Fixed Effects: (Intr) typstr typestrong -0.682 typeweak -0.714 0.541
Apparently, my model shows that the IV has a significant effect. However, when I convert each coefficient of the fixed effects into odds ratio, the outcome is too high in my view as you can see below.
exp(6.1598) # 473.3334 exp(4.2876) # 72.79156
Originally, I expected those coefficients I've mentioned to be negative (or at least much less than 6.1598 and 4.2876). But I got strong doubt on whether I have taken a proper procedure when the model showed those results. So, here are my questions.
Is it okay that the direction of the fixed effects is opposite to the intercept in my model?
Most importantly, is the odds ratio I've calculated usable? i.e. can my IV function as a proper predictor?
Or have I missed or done something wrong?
It's my first time to run a logistic mixed-effects model of which IV has three levels. Any help would be enormously appreciated, thanks in advance!