similar to: zero-inflated mixed models

Dear Mr. or Ms.,   I would like to use the R-software to run the zero inflated mixed model and hurdle mixed model. But I do not know how to do? Would you please tell me the code and data format?   I will be very appreciated if you can help me. Thank you very much.   Best regards,   Sincerely, Xiongqing Zhang [[alternative HTML version deleted]]

Dear R-users, Earlier this year I posted a message to this list regarding negative binomial mixed models in R. It was suggested that the program I had written should be turned into an R-package. This has now been done, in collaboration with David Fournier and Anders Nielsen. The R-package glmmADMB provides the following GLMM framework: - Negative binomial or Poisson responses. - Zero-inflation

I am attempting to build a package on r-forge and running into a weird error. I have been in correspondence with the R-forge admins and am turning to r-devel on the remote chance that someone might have a guess as to what is going wrong or a suggestion about further diagnostics/experiments I could try ... The package seems to build fine on my system(s) with R CMD build --compact-vignettes

Dear list members, I'm interested in showing that within-group statistical dependence is negligible, so I can use ordinary linear models without including random effects. However, I can find no mention of testing a model with vs. without random effects in either Venable & Ripley (2002) or Pinheiro and Bates (2000). Our in-house statisticians are not familiar with this, either,

Dear All, As you know, glmmADMB package use ML method for estimation. Is it possible to use REML estimation method for zero-inflated Poisson distribution? For ML method, poi_ML <- glmm.admb(los ~ psihigh + trt.mod + trt.high + psihigh*trt.mod + psihigh*trt.high + 1, random = ~1, group="site", family="poisson", data=edcap) summary(poi_ML) How can I control to use REML

Dear R-users, Half a year ago we put out the R package "glmmADMB" for fitting overdispersed count data. http://otter-rsch.com/admbre/examples/glmmadmb/glmmADMB.html Several people who used this package have requested additional features. We now have a new version ready. The major new feature is that glmmADMB allows Bernoulli responses with logistic and probit links. In addition there

Group, I am new to R. In my work as a program evaluator, I am regularly asked to estimate effect sizes of prevention/intervention and educational programs on various student outcomes (e.g. academic achievement). In many cases, I have access to data over three or more time periods (e.g. growth in proficiency test scores). I usually have multiple independent and dependent variables in each

Does someone have code, or point to a source to get it, to model repeated measures zero-inflated poisson data. The data come from a replicated field trial comparing two treatments - a control and a test treatment. Thanks in advance ------------------------------------ Subhash Chandra, DSc Senior Biometrician Primary Industries Research Victoria Department of Primary Industries 1 Ferguson Road

Dear R community, I have some questions regarding the analysis of a zero-inflated count dataset and repeated measures design. The dataset is arranged as follows : Unit of analysis: point - these are points were bird were counted during a certain amount of time. In total we have about 175 points. Each point is located within a certain habitat fragment (here: "site"= A-B-C-D-..., in

Greetings glmmADMB function users, I am trying to run a series of models using the glmmADMB function with several different distribution families (e.g., poisson, negbinom). I am using a Optiplex 790 PC with Windows 7, 16.0 GB of RAM and a 64-bit operating system. I am running R version 2.15.0 and started out using the most recent version of glmmADMB (I believe version 7.2.15). My data is zero

To whom it may concern: I am using lmer for a statistical model that includes non-normally distributed data and random effects. I used this same function in the most recent version of R as of fall 2005, and have re-done some of the same analyses using all of the same files, but with the newest version of R (2.2.1). I get answers that are not exactly the same (although I do get the same

Hello, I have count data that illustrate the presence or absence of individuals in my study population. I created a grid cell across the study area and calcuated a count value for each individual per season per year for each grid cell. The count value is the number of time an individual was present in each grid cell. For illustration my data columns look something like this and are repeated for

Hi all, I am not a very proficient R-user yet, so I hope I am not wasting people?s time. I want to run a linear mixed model with 3 random factors (A, B, C) where A and B are partially crossed and C is nested within B. I understand that this is not easily possible using lme but it might be using lmer. I encountered two problems when trying: Firstly, I can enter two random factors in lmer but

Hi R users! I am trying to learn some multilevel analysis, but unfortunately i am now very confused. The reason: http://www.ats.ucla.edu/stat/hlm/seminars/hlm_mlm/mlm_hlm_seminar.htm http://www.ats.ucla.edu/stat/sas/seminars/sas_mlm/mlm_sas_seminar.htm and MlmSoftRev. pdf from mlmRev package. >From what i see, the first two links seem to declare the level one variable as a random part (i

Hi there, I am new to the package glmmadmb, but need it to perform a zero-inflated gzlmm with a binomial error structure. I can't seem to get it to work without getting some strange error messages. I am trying to find out what is affecting the number of seabird calls on an array of recorders placed at 4 sites on 6 islands. I have nightly variables (weather and moonlight), site variables

Hi all, First post for me here, but I have been reading on the forum for almost two years now. Thanks to everyone who contributed btw! I have a dataset of 4000 observations of count of a mammal and I am trying to predict abundance from a inflated-zero model as there is quite a bit of zeros in the response variable. I have tried multiple options, but I might do something wrong as every

Hello everybody, I am using glmmADMB and when I run some models, I recieve the following message: Erro em glmmadmb(eumencells ~ 1 + (1 | owners), data = pred3, family = "nbinom", : The function maximizer failed (couldn't find STD file) Furthermore: Lost warning messages: Command execution 'C:\Windows\system32\cmd.exe /c

Dear all, I am having some problems trying to run a GLMM model with zero-inflation using the alpha version of glmmADMB (0.6.4) using R (2.13.1) in Windows and I would greatly appreciate some help. My count response variable (number of birds: count) fits a negative binomial distribution and the explanatory variables are both continuous and categorical (species= 17). The three random effects are

Hello R users, Doing My PhD I collected count data which I believe is zero inflated. I have run a statistical model with lmer and family=poisson and got summary(model)@sigma=1 so I believe there is no overdispertion. I would like to use the fmr function from the 'gnlm' library but I just cannot figure out from the examples in the help page and some forums out there how to convert the lmer

Hi, I have to analyse the number of provisioning trips to nestlings according to a number of biological and environmental factors. I was thinking of building a mixed-effects model with species and nestid as random effects, using a Poisson distribution, but the data are overdispersed (variance/mean = 5). I then thought of using a mixed-effects model with negative binomial distribution, but I have