Dear Reader,
I'm trying to run a GLMER model for the following data:
*2x scaled continous predictor* (sum score of 2 questionairres)
*1x predictor being 10 trials* on a ultimatum game of which each trial is 1
out of 10 possible options. (offer of a split of $20: e.g. you 1 and 19
me). Inserted this a non ordered factor (10-levels) with sum-to-zero coding
(contrast.sum).
*1x dependent binary variable *being the response to the 10 trials valued
at accepted (1) or reject (2). Entered as a factor.
After the following model without correlations terms (I ran this model
after failing to converge on a model without optimizers and the all_fit of
that) I get the following errors:
glmer(AoR ~ Trials * (sPredictor1*sPredictor2) + (1 | ID )+ (0 + Trials
|ID),family = binomial, data = data, control = glmerControl(optCtrl =
list(maxfun = 1e+9, optimizer = "bobyqa")))
*fixed-effect model matrix is rank deficient so dropping 10 columns /
coefficients*
*Warning messages:*
*1: In (function (npt = min(n + 2L, 2L * n), rhobeg = NA, rhoend = NA, :*
* unused control arguments ignored*
*2: In (function (iprint = 0L, maxfun = 10000L, FtolAbs = 0.00001, FtolRel
= 1e-15, :*
* unused control arguments ignored*
3: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
unable to evaluate scaled gradient
4: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge: degenerate Hessian with 11 negative eigenvalues
I'm afraid I might be doing something wrong in handeling the DV or
10-factor level IV, which in turn, is causing the 3 errors in bold. Does
anyone have suggestions. Or can some one tell me what the source of these
errors are?
Much obliged in advance,
Kindest regards,
Michiel Kiggen
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