R^2 for linear mixed effects models with glmer()
Dear Mix Models Members, ?????? I try to extract R^2 for linear mixed effects models with glmer() function with poisson distribution using r.squaredGLMM() in MuMIn package, but doesn't work. My output always show: #Model ajusted > mT <-glmer(riqueza ~tipo_trat+(1|Ponto),data=d1, + family=poisson, control = glmerControl(check.conv.singular = "warning",optCtrl = list(maxfun=100000))) Warning messages: 1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :Model failed to converge with max|grad| = 0.00894145 (tol = 0.001, component 1) 2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :singular fit 3: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :Model is nearly unidentifiable: very large eigenvalue - Rescale variables?;Model is nearly unidentifiable: large eigenvalue ratio - Rescale variables? #R^2 conditional and marginal > r.squaredGLMM(mT) Error in glmer(formula = riqueza ~ tipo_trat + temp_final + temp_inici + : fitting model with the observation-level random effect term failed. Add the term manually In addition: Warning message: In value[[3L]](cond) :(p <- ncol(X)) == ncol(Y) is not TRUE ???? I change almost all parameters indicating by web posts like glmerControl, maxfun, etc. There are other approaches to calculate the conditional and marginal R^2 for my model with lme4 package? Thanks in advance, Alexandre
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Alexandre dos Santos
Prote??o Florestal
IFMT - Instituto Federal de Educa??o, Ci?ncia e Tecnologia de Mato Grosso
Campus C?ceres
Caixa Postal 244
Avenida dos Ramires, s/n
Bairro: Distrito Industrial
C?ceres - MT CEP: 78.200-000
Fone: (+55) 65 99686-6970 (VIVO) (+55) 65 3221-2674 (FIXO)
alexandre.santos at cas.ifmt.edu.br
Lattes:http://lattes.cnpq.br/1360403201088680
OrcID: orcid.org/0000-0001-8232-6722
Researchgate:www.researchgate.net/profile/Alexandre_Santos10
LinkedIn: br.linkedin.com/in/alexandre-dos-santos-87961635
Mendeley:www.mendeley.com/profiles/alexandre-dos-santos6/
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