I am modeling grade as a function of membership in various cohorts. There
are four "cohorts". (NONE, ISE07,ISE08,ISE09) and two times of cohorts
coded as ISE = TRUE (ISE0#) or FALSE (NONE). There is clear co-linearity
but that is to be expected.
running the following code
CutOff <-0
fit.base <- lme(fixed= zGrade ~ Rep + COHORT/ISE + P7APrior + Female +
White + HSGPA + MATH + AP_TOTAL + Years + EOP + Course,
random= ~1|SID,
data = share[share$GRADE >= CutOff,])
I get the following error
Error in MEEM(object, conLin, control$niterEM) :
Singularity in backsolve at level 0, block 1
but if I take out the /ISE I get no error, simmilarly if I take out the
COHORT/.
I want to test for the effects of the different cohorts within the ISE
subset and across ISE & NONE.
Robert
help with the nested anova formulas
3 messages · Robert Lynch, Ben Bolker
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Robert Lynch <robert.b.lynch <at> gmail.com> writes:
I am modeling grade as a function of membership in
various cohorts. There
are four "cohorts". (NONE, ISE07,ISE08,ISE09) and two times of cohorts
coded as ISE = TRUE (ISE0#) or FALSE (NONE). There is clear co-linearity
but that is to be expected.
running the following code
CutOff <-0
fit.base <- lme(fixed= zGrade ~ Rep + COHORT/ISE + P7APrior + Female +
White + HSGPA + MATH + AP_TOTAL + Years + EOP + Course,
random= ~1|SID,
data = share[share$GRADE >= CutOff,])
I get the following error
Error in MEEM(object, conLin, control$niterEM) :
Singularity in backsolve at level 0, block 1
but if I take out the /ISE I get no error, simmilarly if I take out the
COHORT/.
I want to test for the effects of the different cohorts within the ISE
subset and across ISE & NONE
I can send the data (the whole is too large) if you wish.
Please send this to r-sig-mixed-models at r-project.org for more discussion. The short answer is that lme can't fit models with rank-deficient fixed effect model matrices -- in other words, there are redundant parameters in your model because COHORT and ISE between them use 6 parameters to model 4 independent quantities. http://stats.stackexchange.com/questions/35071/ what-is-rank-deficiency-and-how-to-deal-with-it