[R-sig-ME] Can we do b-spline within lmer function?
a.fugard at ed.ac.uk
Fri Jan 18 20:19:59 CET 2008
Ken Beath wrote:
> On 15/01/2008, at 9:42 AM, Zhong, Xiao wrote:
>> Thanks, Ken.
>> I tried your advice on my model:
>> model2.growth.mcas5 <- lmer(response ~ bs(monthElapsed) + skills +
>> (1|studentID), data= mcas5, family=binomial(link="logit"), control =
>> list(msVerbose = 1, usePQL = FALSE))
>> It worked! What it gave me is:
>> bs(monthElapsed)2 bs(monthElapsed)3
>> -0.1934738 0.6257330
>> skillsG-Geometry skillsM-
>> Measurement skillsN-Number-Sense-Operations skillsP-Patterns-
>> 0.5263370 0.1897903
>> Since I am trying to use design matrix to predict after that glmm
>> fitting, could you tell me if there is some function/command that I
>> can use to find what the three "bs" did to my "monthElapsed" variable?
> As Vito mentioned you probably need a few more knots, see the help on
> bs. The spline models I have fitted have been in lme and have used
> predict to obtain the shape of the curves, but this doesn't seem
> available in lmer.
I have been reading this thread with interest. When bs uses only a
cubic, presumably it's easy to wire up a custom predict function based
on the fixed effects, using coef - for this example piping the output
through the inverse logit function to get back something in [0,1]. But
what does the formula look like when you use proper splines? I can't
get that from the help.
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