similar to: glmm for binomial data? (OT)

Dear users of the R mailing list, I am a ph.d. student in biology working on red deer in Norway, who would like to conduct an analysis with random factor where the response is binomially distributed. This cannot be conducted in S-plus, and I was told by others that it may be possible in R. However, I soon got into trouble which I hope you can help me to solve. My model is on this form:

Currently I have a data set looking like: License Species Year HD Quota L.R.QTA L.R.QTA Success Surplus Permit Elk 1999 101 50 87 90 151 10 Permit Deer 1999 101 50 20 10 151 8 Permit Elk 1999 101 50 87

Hi all, This may seem like a dumb question, but I work for an entity that is soon converting to XP across the board, and I will lose the ability to install software on my own. The entity has a policy of only using software that has been purchased and "properly licensed" (whatever that means). This means I will soon lose the ability to use R at work - something I can't do without

Hi, I'm trying to teach myself R, and by the way, re-learning statistics using Crawley's "Statistics: an introduction using R". I've reached the regression chapter, and when it deals with non-linear regresion using the nls library I face the following problem: I follow the steps--- >deer<-read.table("c:\\temp\\jaws.txt",header=T) ---data available at

Hi Eric, the following works for me. HTH, Eric library(EGRET) StartDate <- "1990-10-01" EndDate <- "2017-09-30" siteNumber <- "10310000" QParameterCd <- "00060" Daily <- readNWISDaily(siteNumber, QParameterCd, StartDate, EndDate) # Define 'center of mass' function com <- function(x) { match(TRUE, cumsum(x/sum(x)) > 0.5) -

Dear R-list, I thought that I would let some of you know of a free R package, glmm.ADMB, that can handle mixed models for overdispersed and zero-inflated count data (negativebinomial and poisson). It was built using AD Model Builder software (Otter Research) for random effects modeling and is available (for free and runs in R) at: http://otter-rsch.com/admbre/examples/glmmadmb/glmmADMB.html I

Hi R-users,   I intend to apply a mixed model on a set of longitudinal data, with a negative binomial distributed dependent variable, and after following the discussions on R help list I saw that more experienced people recommended using lmer (from lme4 pack), glmmPQL (from MASS) or glmm.admb (from glmmADMB pack)     My first problem: yesterday this syntax was ok, now I get this weird message (I

I'm having trouble using binomial(link="cloglog") with GLMM in lme4, Version: 0.5-2, Date: 2004/03/11. The example in the Help file works fine, even simplified as follows: fm0 <- GLMM(immun~1, data=guImmun, family=binomial, random=~1|comm) However, for another application, I need binomial(link="cloglog"), and this generates an error for me: >

Hello I have a problem when fitting a mixed generalised linear model with the lmer-function in the Matrix package, version 0.98-7. I have a respons variable (sfox) that is 1 or 0, whether a roe deer fawn is killed or not by red fox. This is expected to be related to e.g. the density of red fox (roefoxratio) or other variables. In addition, we account for family effects by adding the mother

Hello, At present, can generalized linear mixed models with negative binomial distribution and estimating the shape parameter be fit using R? I am aware of glm.nb but am wondering about incorporation of mixed effects. Thanks in advance, Brian Aukema

In the following plot, the y label is missing if it is too long. x11(type="Xlib") plot(1:5, 1:5, ylab="Do, a deer, a female deer") # missing label plot(1:5, 1:5, ylab="Do") # label is present All is well for x11(type="cairo") This is true both under R devel 2017-09-01 on xubuntu (my desktop), and 3.4.1 on Centos 6.9 (department

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)

Hi there. At first glance it sounded to me as an obvious "no-no" question. But, for some reason, I ran some trials and results looked pretty intriguing. So, I checked 14 genotypes (8 plants from each randomly chosen in the field) on 4 different dates and measured them under 2 different temperatures. As a response, I have 4 different partition of how light is absorbed in the leaf and

Hello R users I'm using MuMIn but for some reason I'm not getting the adjusted confidence interval and uncoditional SE whe I use model.avg(). I took into consideration the steps provided by Grueber et al (2011) Multimodel inference in ecology and evolution: challenges and solutions in JEB. I created a global model to see if malaria prevalence (binomial distribution) is related to any

Dear User R It's been a pleasure talking with you. I am newcomer use R. Would you please help me how to translate the script below to "R" script? * Area under receiver operating characteristic (AU-ROC) predict r1m1p, p roctab malaria r1m1p, graph summary * Area under receiver operating characteristic (AU-ROC) curve predict r1m2p, mu roctab malaria r1m2p, graph summary

*Dear Bert, * Thank you very much for your feedback and the useful link https://rseek.org/ and https://www.r-bloggers.com/calculating-auc-the-area-under-a-roc-curve/. Actually, I want to know different performance between Stata and R, in multilevel logistic regression. For this purposes, I replicate ".do" file use Stata in

Hi, In my analysis of impacts of insecticide-treated bednets on malaria, I look at the relationship between malaria incidence and mosquito behaviors. The condensed data set is copied here. Ordinary regression (lm) shows that Incidence was negatively related to Mortality. This makes sense because the latter reflected the strength of killing mosquitoes by insecticide-treated nets. Since the

Hello to all R users, I use R for a year now and am dealing with geometric morphometrics of deer skulls. Yes, I am a biologist and my math skills are just beginning to brush up. To cut to the chase... I have two groups in my data (males and females) and my data is in a simple vector form. Now I need a bootstrap test for this value szc1 <- ((mean(maleCent)-mean(femaCent))^

Eric B's response provided just the kind of quick & simple solution I was hoping for (appears as the function com below). However, I once again failed to take advantage of the power of R and have reverted back to using a for loop for the next step of the processing. The example below (which requires the library EGRET for pulling an example dataset) works, but probably can be replaced

We've just cut over to a new mail server running Dovecot 1.0.5. The underlying OS is RHEL 5. User mailboxes are stored in Unix mbox format on a local ext3 file system. The MTA on the system is the default RedHat version of Sendmail 8.13.8 with procmail for local delivery. We're using a combination of dotlock and fcntl style locking. The output of "dovecot -n" for this system