Rasch with lme4
Andy Fugard wrote:
Daniel Ezra Johnson wrote:
In the output for this model:
M2 = lm(Reaction ~ Days + Sex + factor(Subject), sleepstudy) summary(M2)
You will see that one of the coefficients is NA. If you put factor(Subject) before Sex it would be SexMale that comes out NA. Nested fixed effects will always return an error (or incomplete model), unless I'm completely mistaken.
You were correct! (Estimate for "factor(Subject)371" is broken.)
Thanks for a tip off-list from Daniel and Chuck that I check how I made
up the participants' sex :-)
So then does something similar happen for some cases when you try to
model items as fixed effects?
A
> # Try again again
> M1 = lmer(Reaction ~ Days + (1|Subject), sleepstudy)
>
> # Use the random intercept to make up a Male/Female IV
> ranefs = ranef(M1)$Subject
> sexDF = data.frame(Sex =
cut(ranefs$"(Intercept)",2,labels=c("Female","Male")),
+ Subject = rownames(ranefs))
>
> sleepstudy.sex = merge(sleepstudy,sexDF)
>
>
> M2 = lm(Reaction ~ Days + Sex + factor(Subject), sleepstudy.sex)
> summary(M2)
Call:
lm(formula = Reaction ~ Days + Sex + factor(Subject), data = sleepstudy.sex)
Residuals:
Min 1Q Median 3Q Max
-85.970 -13.790 1.767 12.957 53.056
Coefficients: (1 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|)
(Intercept) 257.3095 14.5333 17.705 < 2e-16 ***
Days 10.6920 0.9627 11.106 < 2e-16 ***
SexMale 59.7598 18.0982 3.302 0.001472 **
factor(Subject)309 -85.8306 18.8055 -4.564 1.92e-05 ***
factor(Subject)310 -79.1101 19.8317 -3.989 0.000153 ***
factor(Subject)330 -63.0263 16.9719 -3.714 0.000391 ***
factor(Subject)331 -47.4795 16.1890 -2.933 0.004452 **
factor(Subject)332 -73.4632 16.1945 -4.536 2.13e-05 ***
factor(Subject)333 -45.4487 16.9719 -2.678 0.009098 **
factor(Subject)334 -5.9602 19.8186 -0.301 0.764446
factor(Subject)335 -58.4926 18.8025 -3.111 0.002638 **
factor(Subject)337 14.6896 16.1818 0.908 0.366900
factor(Subject)349 -28.7516 18.8055 -1.529 0.130498
factor(Subject)350 -67.3889 16.1826 -4.164 8.26e-05 ***
factor(Subject)351 -26.1381 18.8055 -1.390 0.168665
factor(Subject)352 -35.0784 16.1890 -2.167 0.033425 *
factor(Subject)369 -52.4248 16.1945 -3.237 0.001799 **
factor(Subject)370 -25.4865 18.8055 -1.355 0.179400
factor(Subject)371 NA NA NA NA
factor(Subject)372 -45.9271 16.9741 -2.706 0.008433 **
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
Residual standard error: 28.03 on 75 degrees of freedom
Multiple R-squared: 0.8089, Adjusted R-squared: 0.763
F-statistic: 17.63 on 18 and 75 DF, p-value: < 2.2e-16
>
> # Broken as promised!