[R-sig-ME] glmer and influence.me - complaining about nAGQ==0
Cátia Ferreira De Oliveira
cm|o500 @end|ng |rom york@@c@uk
Fri May 14 16:19:28 CEST 2021
Dear Professor Bolker,
I am currently running the allfit function for the models I mentioned in
the previous email and I am now doing the same for another model using the
same data and this seems much worse. This is the model that seems to give
even worse fit with this value "Model failed to converge with max|grad| *=
0.167262* (tol = 0.002, component 1)" being much higher. Are there any
other suggestions I could take? This model I am running without the logRT
and the nAGQ==0.
Thank you!
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: Gamma ( log )
## Formula:
## RT ~ Probability * Session * Group * Age + (1 + Session *
Probability | Participant)
## Data: Data.trimmed
## Control: glmerControl(optimizer = "bobyqa", optCtrl = list(maxfun = 2e+05))
##
## AIC BIC logLik deviance df.resid
## 938050.5 938301.3 -468998.3 937996.5 79890
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.258 -0.597 -0.151 0.410 33.938
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## Participant (Intercept) 1.700e-03 0.041232
## Session1 2.583e-04 0.016073 0.13
## Probability1 1.121e-04 0.010589 -0.06 0.11
## Session1:Probability1 6.176e-05 0.007859 0.02 -0.02 -0.02
## Residual 5.448e-02 0.233418
## Number of obs: 79917, groups: Participant, 45
##
## Fixed effects:
## Estimate Std. Error t value Pr(>|z|)
## (Intercept) 5.9334448 0.0739725 80.211 < 2e-16 ***
## Probability1 -0.0162354 0.0100753 -1.611 0.10709
## Session1 0.0631180 0.0209673 3.010 0.00261 **
## Group1 -0.0331517 0.0740287 -0.448 0.65428
## Age 0.0035260 0.0023510 1.500 0.13367
## Probability1:Session1 0.0059755 0.0075507 0.791 0.42872
## Probability1:Group1 0.0060958 0.0101003 0.604 0.54616
## Session1:Group1 0.0215458 0.0210650 1.023 0.30639
## Probability1:Age -0.0003351 0.0003189 -1.051 0.29331
## Session1:Age -0.0006021 0.0006607 -0.911 0.36220
## Group1:Age -0.0009086 0.0023529 -0.386 0.69938
## Probability1:Session1:Group1 0.0067270 0.0075839 0.887 0.37507
## Probability1:Session1:Age -0.0001585 0.0002380 -0.666 0.50544
## Probability1:Group1:Age -0.0002775 0.0003196 -0.868 0.38519
## Session1:Group1:Age -0.0007188 0.0006636 -1.083 0.27877
## Probability1:Session1:Group1:Age -0.0001956 0.0002391 -0.818 0.41320
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation matrix not shown by default, as p = 16 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
## optimizer (bobyqa) convergence code: 0 (OK)
## Model failed to converge with max|grad| = 0.167262 (tol = 0.002, component 1)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?
## Model is nearly unidentifiable: large eigenvalue ratio
## - Rescale variables?
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