warnings when using binomial models and offset - NaNs
More generally: I would ask whether it makes sense to scale the density at all; if your density is measured in sensible areal units (e.g. individuals/hectare), then leaving it as-is will mean that your other parameters will be in units of their effects on capture/(individuals/hectare). Maybe you've been standardizing all of your predictors according to the (generally wise) advice that standardizing makes parameters more comparable/interpretable -- but offsets are an exception to this advice ...
On 2018-11-26 7:35 a.m., Mollie Brooks wrote:
If you?re using the scale() function to standardize your density values, you could use the argument, center=FALSE, to avoid subtracting the mean and thus avoid negative densities. cheers, Mollie
On 26Nov 2018, at 13:33, Joana Martelo <joanamartelo at gmail.com> wrote: Thanks for your email! Warnings' problem is solved, however, when I use log(density) or log(density+1) I got NaNs because density has negative numbers. Density is 2,4,6 which standardized gives -1.793073717, -0.450015136, 0.893043446. So, log(-1.793073717+1)= NaN Any suggestions? Many thanks! Joana -----Mensagem original----- De: R-sig-mixed-models [mailto:r-sig-mixed-models-bounces at r-project.org] Em nome de Ben Bolker Enviada: sexta-feira, 23 de Novembro de 2018 21:54 Para: r-sig-mixed-models at r-project.org Assunto: Re: [R-sig-ME] warnings when using binomial models and offset This is a pretty common error, which I've now added to the GLMM FAQ. You should be using log(density), not density, as your offset term; if you use density, then you end up specifying that your capture counts are proportional to exp(density), which is often a ridiculously huge number. cheers Ben Bolker On 2018-11-23 12:26 p.m., Joana Martelo wrote:
Hello everyone I'm trying to model fish capture success using length, velocity and group composition as explanatory variables, density as an offset variable, and fish.id. as random effect. I'm getting the follow warnings: Model1<-glmer(capture~length+offset(density)+(1|fish.id),family=binomi al,dat a=cap) Warning messages: 1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, : Model failed to converge with max|grad| = 0.260123 (tol = 0.001, component 1) 2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, : Model is nearly unidentifiable: very large eigenvalue - Rescale variables? - I only get the warnings when I use length and group composition, not with velocity. - I don't get any warning if I don't use the offset. I've tried: Model1<-glmer(capture~length+offset(log(density))+(1|fish.id.c),family =binom ial(link="cloglog"),data=cap) But still get the warning. Any ideas of what might be the problem? Many thanks! Joana Martelo Melhores cumprimentos, Joana Martins [[alternative HTML version deleted]]
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