Multi-level Rasch Model Per Douglas Bates' paper
?? If you change that last line to lme4::glmer() it works fine. ?? In the early days lmer() specified with a family argument would automatically convert (internally) to a glmer call, but we shut that off in a recent release.
On 5/13/20 12:35 PM, Rasmus Liland wrote:
On 2020-05-13 17:28 +0200, Phillip Alday wrote:
On 13/5/20 5:07 pm, Simon Harmel wrote:
Hi All! I'm following this paper https://www.jstatsoft.org/article/view/v020i02 by Prof. Bates where after fitting the model (*pp. 14-15*), they obtain what they call *item easiness* *"from the estimates of the fixed effects and the conditional modes of the random effects."*
Dear Simon,
I was not even able to get past subsection 3.2 ...
how reproducible even are the examples in
this text?
Best,
Rasmus
data("lq2002", package="multilevel")
wrk <- lq2002
# wrk[1:5,]
for (i in 3:16) wrk[[i]] <- ordered(wrk[[i]])
for (i in 17:21) wrk[[i]] <- ordered(5 - wrk[[i]])
lql <- reshape(wrk,
varying = list(names(lq2002)[3:21]),
v.names = "fivelev",
idvar = "subj",
timevar = "item",
drop = names(lq2002)[c(2, 22:27)],
direction = "long")
lql$itype <-
with(lql, factor(ifelse(item < 12, "Leadership",
ifelse(item < 15, "Task Sig.", "Hostility")
)))
for (i in c(1, 2, 4, 5)) lql[[i]] <- factor(lql[[i]])
lql$dichot <- factor(ifelse(lql$fivelev < 4, 0, 1))
# str(lql)
# summary(lql)
## 3.2 Fitting an initial multilevel Rasch model
(fm1 <- lme4::lmer(
dichot ~ 0 + itype + (1 | subj) + (1 | COMPID) + (1 | item),
lql,
binomial))
Error in mkRespMod(fr, REML = REMLpass) : response must be numeric
Calls: <Anonymous> -> do.call -> <Anonymous> -> mkRespMod
Execution halted
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