Hello! I've run some mixed models using lmer and they don't give p-values. I would like to know if there is a way to get p-values for these models. Someone suggested using the afex package. I've looked into this and am confused and overwhelmed. At https://rdrr.io/rforge/afex/man/mixed.html, for example, it gives what looks like very complicated and involved code; it's so overwhelming it makes me wonder if this is really what I need to do! Below is an example of a mixed model I run; I would like to get p-values for the fixed effects and the correlations of fixed effects. Any help would be appreciated! Thank you!
Linear mixed model fit by REML ['lmerMod']
Formula: score ~ group + condition + (1 | subject) + (1 | token_set) + (1 | list)
Data: EN_JT_1
REML criterion at convergence: 744.9
Scaled residuals:
Min 1Q Median 3Q Max
-3.5860 -0.0364 0.2183 0.5424 1.6575
Random effects:
Groups Name Variance Std.Dev.
subject (Intercept) 0.006401 0.08000
token_set (Intercept) 0.001667 0.04083
list (Intercept) 0.000000 0.00000
Residual 0.084352 0.29043
Number of obs: 1704, groups: subject, 71; token_set, 24; list, 2
Fixed effects:
Estimate Std. Error t value
(Intercept) 0.99796 0.02425 41.156
groupHS -0.08453 0.02741 -3.084
groupSB -0.03103 0.03034 -1.023
conditionEN-GJT-D-ENG -0.10329 0.01990 -5.190
conditionEN-GJT-D-NNS -0.01288 0.02617 -0.492
conditionEN-GJT-D-NTR -0.19250 0.02596 -7.415
Correlation of Fixed Effects:
(Intr) gropHS gropSB cEN-GJT-D-E cEN-GJT-D-NN
groupHS -0.452
groupSB -0.409 0.361
cEN-GJT-D-E -0.410 0.000 0.000
cEN-GJT-D-NN -0.531 0.000 0.000 0.380
cEN-GJT-D-NT -0.535 0.000 0.000 0.383 0.700
optimizer (nloptwrap) convergence code: 0 (OK)
boundary (singular) fit: see ?isSingular