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Questions tagged [glmmadaptive]

GLMMadaptive is an R package for generalized linear mixed models. Please also include some statistics methods tags.

12 questions
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GLM modeling binomial proportions with varying trials and probabilities

A collection of coin manufacturers, $m$, each produces a line of coins, the number of which varies by manufacturer (some produce 3 types of coins, others make 7, and so on). Each manufacturer imparts a characteristic bias towards flipping heads on…
a crab
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Advice for R packages for GLMM and (adaptive) Gauss Hermite quadrature

I was looking here for a R package to make an estimate on a general linear mixed effects model (Poisson family) with two random effects and (adaptive) Gaussian quadrature. I also need the full matrix of variance-covariance of the fixed and random…
Flora Grappelli
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How to implement a mixed-model with a beta distribution?

I am interested in using a generalised linear mixed model with a response variable (values ranging from 0.001-0.999) that best fits a beta distribution when checked using the 'fitdistrplus' package and the 'descdist()' function in R. I understand…
sbooth
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Interpretation of Positive Count Coefficients in Hurdle Model

What is the proper interpretation of the coefficients for the positive count part of a hurdle model (truncated Poisson or Negative Binomial)? I have read that the interpretation of the coefficients for a nontruncated Poisson (one unit increase in x…
Andy
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Zero-inflated or two-part models: how to interpret main effects of categorical fixed effects?

I'm running a hurdle lognormal model using the GLMMadaptive package in R. Both the continuous part as well as the zero-part have categorical variables defined in the fixed effects. I would like to run an ANOVA on these categorical variables to…
RmyjuloR
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GLMMadaptive - Hessian matrix problem Hurdle Beta Model

Data: I have a percentage (or proportion see paragraph below) outcome dataset with a high number of zero's. I have therefore attempted to run a hurdle beta model using the GLMMadaptive package in R. I would like to predict this percentage outcome…
RmyjuloR
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Mixed effect zero inflated negative binomial model in R: use of Dharma package, glmmTMB and glmmAdaptive

I am having trouble fitting a mixed effect zero inflated negative binomial model to my data using the GLMMadaptive package: negbi_1 <- mixed_model(fixed=MA ~ ST + AG + SU +SO +Y, random = ~ 1|FA, …
user241508
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Using variance-covariance matrix of mixed-effects logistic regression to obtain p-values for custom contrasts

My question is a follow-up to this question, following through on @Isabelle Ghement's excellent series of responses. I just want to run this past some people in the know to see if what I am doing is correct. I am conducting a longitudinal logistic…
llewmills
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Mixed effect zero inflated negative binomial model: "the leading minor of order 1 is not positive definite"

I am having trouble fitting a mixed effect zero inflated negative binomial model to my data using the GLMMadaptive package: mixed_model(abun ~ TREATMENT + Size + R , random = ~1 | PLOT.TR, data = abunIP, family =…
KK Li
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Computation and interpretation of marginal effects in a GLMM

I am currently working on a GLMM model which uses a Poisson distribution and need to compute and interpret marginal effects from this model. The model outcome consists of a count (COUNT) collected yearly for a number of different entities. The…
Isabella Ghement
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GLMER, GHAQ and marginaled coefficients

I am confused about the GLMM procedures and their reporting. I have tried to follow @Ben Bolker on mixed effect model. However, I am confused after the GLMAdaptive approach. I will lay out my problem. The experiment involved breeding organisms in…
Harshad
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Differences between glmmadaptive Vs lme4 and glmmTMB in ICC measurement

This is my first question, so please be kind... I am currently modelling a GLMM with a binary outcome with many (500+) clusters but cluster size of 2 (by design - there can be no more than 2 per cluster). I am specifically interested in the ICC and…
am767
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