similar to: glmmTMB

Hi folks, I love the Phia package andwant to use it with glmmTMB, but when i try to use the interactionMeans command, i get the below error modelrepeatedmain2 <- glmmTMB(counts ~ cluster*nominated*nominator*junior_senior+Ltime+ (1|school)+(1|id), data=d_shortf, family=nbinom1)

Dunno ... But you might do better posting this on the r-sig-mixed-models list where it both should fit better and where you are more likely to find the relevant expertise. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Thu,

Dear Listers, I have a general statistical question. Are hurdle logit-poisson model and posson model nested? Thank you so much?

Dear all, A question related to the following has been asked on R-help before, but I could not find any answer to it. Input will be much appreciated. I got an unexpected sign of the "slope" parameter associated with a covariate (diam) using zeroinfl(). It led me to compare the estimates given by zeroinfl() and hurdle(): The (significant) negative estimate here is surprising, given

Duncan Murdoch <murdoch.duncan <at> gmail.com> writes: > > On 04/10/2015 10:10 AM, Jonathan Greenberg wrote: > > Folks: > > [snip snip snip] > > > > Is there a way to do a conditional importFrom based on the OS? Or can I > > safely ignore this (I'm trying to submit to CRAN). > > > > Yes, you can put conditionals into the

This request is related to the following post from last year: https://stat.ethz.ch/pipermail/r-help/2011-June/279752.html After reading the thread, the idea is still not clear. I have fitted a model using HURDLE from the PSCL package. I am trying to get marginal effects / slopes by multiplying the coefficients by the mean of the marginal effects (I think this is right). To my understanding, this

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

Dear all, I have had some rather serious difficulties getting graphics and analysis packages to load in R on my new Ubuntu Install. The trouble seems to begin when attempting to install TMB. I have done a full purge of r-base r-base-dev and r-base-core and reinstalled the newest version of RStudio (not that this should matter). I'm not sure what to try next. many thanks! Brandon Z >

Goal: use GEE or GLMM to analyze repeated measures data in R GEE problem: can?t find a way to do GEE with negative binomial family in R GLMM problem: not sure if I?m specifying random effect correctly Study question: Does the interaction of director and recipient group affect rates of a behavior? Data: Animals (n = 38) in one of 3 groups (life stages): B or C. Some individuals (~5)

Hello, I have been trying to find out whether it is possible to use more than one offset in a gam (in mgcv). The reason I would like to do this is to 1) account for area surveyed in a Poisson model of sightings of porpoises within defined grid cells (each cell has a slightly different area) and 2) account for detection probability within each grid cell (some grid cells are further away from the

Dear list, I am using the hurdle model for modelling the habitat of rare fish species. However I do get an error message when I try to model my data: > test_new1<-hurdle(GALUMEL~ depth + sal + slope + vrm + lat:long + offset(log(haul_numb)), dist = "negbin", data = datafit_elasmo) Error in hurdle(GALUMEL ~ depth + sal + slope + vrm + lat:long + offset(log(haul_numb)), :

I am interested in utilizing this so called "double hurdle" model in my study. We can write the model in the following way: if (z'a + u > 0 & x'b + e > 0) y = x'b + e, else y = 0 In the model, consumption y is the (left-) censored dependent variable. e and u are the normally distributed error terms. z'a is the participation equation and x'b is the

Hi there, I'm pretty new to the field of fitting (anything). I try to fit a distribution with mle, because my real data seems to follow a zero-inflated poisson distribution. So far, I tried a simple example to see whether I understand how to do it or not: # example count data x <- 0:10 y <- dpois(x, lambda = 1.4) # zero-inflated poisson zip <- function(x, lambda, prop) { (1 -

Hello to everyone. I´m writing you because I´m feeling a bit frustrated with my work. My work consists in finding the relation between the amount of fires and the weather, so, my response variable is the amount of fires in a fire season and the explanatory variables are the temperature, the amount of precipitation and the some others…. my problem is this; I keep getting the wrong sign in the

Hi All, My dependent variable is a ratio that takes a value of 0 (zero) for 95% of the observations and positive non-integer values for the other 5%. What model would be appropriate? I'm thinking of fitting a GLM with a Poisson ~. Now, becuase it takes non-integer values, using the glm function with Poisson family issues warning messages. Warning messages: 1: In dpois(y, mu, log = TRUE) :

Dear all, I am analyzing counts of seabirds made from line transects at sea. I have been fitting Poisson and negative binomial distributions to the data using the goodfit function from the vcd library. I would also like to evaluate how well a quasi-poisson distribution fits the data. However, none of the potentially suitable functions I have identified (goodfit(vcd), fitdistr(MASS),

Hi all-- We are planning an intervention study for adolescent alcohol use, and I am planning to use simulations based on a hurdle model (using the hurdle() function in package pscl) for sample size estimation. The simulation code and power code are below -- note that at the moment the "power" code is just returning the coefficients, as something isn't working quite right. The

CRAN, by relying on the powerful package management system that is part of R, provides an unparalleled framework for extending R with nearly 20k packages. We recently encountered an issue that highlights a missing element in the otherwise outstanding package management system. So we would like to start a discussion about enhancing its feature set. As shown below, a mechanism to force

Greetings R Users! I have a data set of count responses for which I have made repeated observations on the experimental units (stream reaches) over two air photo dates, hence the mixed effect. I have been using Dr. Jim Lindsey's GLMM function found in his "repeated" measures package with the "poisson" family. My problem though is that I don't think the poisson

Hi! I am a psychologist who suspects that the only sensible way to analyse a particular data set is to use generalised linear mixed models. I am hoping that someone might be able to point me in the right direction to find some very practical hands on documentation that might be able to talk me through actually doing such an analysis? So far in my searches the most useful document I have turned