problem with lme4

Dear all,

I am a French student in BioStatistic and I have a question about the package lme4.

I am using the glmer function but it doesn't work ... I have these errors :

model <- glmer(Motif ~ as.factor(AP2) + (1|ID), data=d, family=binomial(link="logit"))

Erreur dans pwrssUpdate(pp, resp, tolPwrss, GQmat, compDev, fac, verbose) :
   Downdated VtV is not positive definite

Or sometimes this one :
Erreur : pwrssUpdate did not converge in 30 iterations

I found on the web, that we can change the tolerance (Tolpwrss) and indeed it works.
But, for different values, my results are completely different (see the examples for tolPwrss = 1e-5 and 1e-2) :

model <- glmer(Motif ~ as.factor(AP2) + (1|ID), data=d, family=binomial(link="logit"),control= glmerControl(tolPwrss=1e-5, optimizer="bobyqa"))

Generalized linear mixed model fit by maximum likelihood ['glmerMod']
Family: binomial ( logit )
Formula: Motif ~ as.factor(AP2) + (1 | ID)
    Data: d

      AIC      BIC   logLik deviance
  78.9974  93.2092 -35.4987  70.9974

Random effects:
Groups Name        Variance Std.Dev.
ID     (Intercept) 578.5    24.05
Number of obs: 258, groups: ID, 218

Fixed effects:
                  Estimate Std. Error z value Pr(>|z|)
(Intercept)        10.205      6.149   1.660    0.097 .
as.factor(AP2)1    15.057  46157.700   0.000    1.000
as.factor(AP2)2     9.356     10.219   0.916    0.360
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Correlation of Fixed Effects:
             (Intr) a.(AP2)1
as.fc(AP2)1  0.000
as.fc(AP2)2 -0.303  0.000

model <- glmer(Motif ~ as.factor(AP2) + (1|ID), data=d, family=binomial(link="logit"),control= glmerControl(tolPwrss=1e-2, optimizer="bobyqa"))

Generalized linear mixed model fit by maximum likelihood ['glmerMod']
Family: binomial ( logit )
Formula: Motif ~ as.factor(AP2) + (1 | ID)
    Data: d

      AIC      BIC   logLik deviance
112.9273 127.1392 -52.4637 104.9273

Random effects:
Groups Name        Variance Std.Dev.
ID     (Intercept) 3.794    1.948
Number of obs: 258, groups: ID, 218

Fixed effects:
                 Estimate Std. Error z value Pr(>|z|)
(Intercept)       2.8039     0.4435   6.322 2.58e-10 ***
as.factor(AP2)1  10.5258   117.9609   0.089   0.9289
as.factor(AP2)2   2.1162     1.0125   2.090   0.0366 *
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Correlation of Fixed Effects:
             (Intr) a.(AP2)1
as.fc(AP2)1 -0.004
as.fc(AP2)2 -0.415  0.002

So I want to know, until which threshold of tolPwrss are results reliable ??
Is it correct to change this value for all my model ? (Sometimes it doesn't work until I put tolPwrss=0.01 or 0.1 ..)

I hope you will understand what I explained and you will be able to help me ..

If there is few things I haven't been clear, don't hesitate to ask me again.

Thank you for your attention to these matters.

Best regards,

Mathilde


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