search for: qaicc

...Overdispersion test Obs.Var/Theor.Var Statistic p-value poisson data 2.628131 23.65318 0.0048847 So, I am running a simple glm with my distribution as quasipoisson > glm.richness1<-glm(beetle.richness~log.area, family = quasipoisson) Now I want to calculate a qAIC and qAICc. I was trying to modify the equation that I found in Bolker et al 2009 supplemental material: QAICc <- function(mod, scale, QAICc=TRUE){ LL <- logLik(mod) ll <- as.numeric(LL) df <- attr(LL, "df") n <- length(mod$y) #used $ to replace @ t...

Quasi-Poisson regression - using parameter estimates for QAICc Hello, I am using lmer (package lme4), for a GLMM, where I am modeling overdispered data with 1 random effect and several fixed effects. I want to use QAICc for my model selection, however I have 2 concerns 1) I don't know how to properly estimate the overdispersion parameter (c_hat), which...

...estimable parameters and sample size is made of about 1500 observations. The global model seems not to have problems of parameters estimability nor get troubles with the convergence of these models. I have run all the models and at the end I get the global model as the more parsimonious one (least QAICc -> I have set c-hat=1.15 according to goodness of fit on the global model). This is the first time it occurs to me and I am somehow confused. I believe the data set is not that poor with respect to the number of parameters (it should not be the Friedman paradox) and the only thing it seems logic...

Hi all, I'm having trouble with the model generating 'dredge' function in the MuMIn 'Multi-model Inference' package. Here's the script: globalmodel<- glm(TB~lat+protocol+tested+ streams+goats+hay+cattle+deer, family="binomial") chat<- deviance(globalmodel)/59 #There we 59 residual degrees of freedom in this global model. models<- dredge(globalmodel,

...e posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Kamil Barton Reply | Threaded | More Mar 30, 2013; 9:48am Re: Error message in dredge function (MuMIn package) used with binary GLM 2 posts 'rank' should be "QAICc". AICc does not have argument 'chat', hence the error. kamil CatCowie Reply | Threaded | More Mar 30, 2013; 10:35am Re: Error message in dredge function (MuMIn package) used with binary GLM Hi Kamil, Thanks for your help. I do want to use rank="QAICc", but I when I tr...

...ller" who has been using R in research and graduate teaching for over 5 years. I hope that my question is simple but not too foolish. I've looked through the FAQ and searched the R site mail list with some close hits but no direct answers, so... I would like to estimate QAIC (and QAICc) for a glm fit using the quasibinomial family. I found a general reference suggesting a simple solution: "we calculated QAICc adjusting for overdispersion by dividing the residual deviance (i.e. -2 loglikelihood) with the overdispersion parameter calculated from the most complex mode...

Dear all, Using the quasibinomial and quasipoisson families results in no AIC being calculated. However, a quasi AIC has actually been defined by Lebreton et al (1992). In the (in my opinon, at least) very interesting book by Burnham and Anderson (1998,2002) this QAIC (and also QAICc) is covered. Maybe this is something that could be implemented in R. Take a look at page 23 in this pdf: http://www.springer-ny.com/supplements/0387953647/Preface_Contents_and_Chapter_8.pdf Lebreton, J-D et al. (1992) Modeling Survival and Testing Biological Hypotheses Using Marked Anomals: A Un...

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