similar to: difficulties with MuMIn model generation with coxph

Displaying 20 results from an estimated 200 matches similar to: "difficulties with MuMIn model generation with coxph"

2013 Mar 29
2
Error message in dredge function (MuMIn package) used with binary GLM
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<-
2013 Nov 07
2
Error running MuMIn dredge function using glmer models
Dear list, I am trying to use MuMIn to compare all possible mixed models using the dredge function on binomial data but I am getting an error message that I cannot decode. This error only occurs when I use glmer. When I use an lmer analysis on a different response variable every works great. Example using a simplified glmer model global model: mod<- glmer(cbind(st$X2.REP.LIVE,
2010 Aug 17
2
AIC in MuMIn
Hello, I am using package MuMIn to calculate AIC for a full model with 10 explanatory variables. Thanks in advance in sharing your experience. Q1 In the AIC list of all models, each model is differentiated by model number. Please kindly advise if it is possible to find the corresponding explanatory variable(s) for the model number. Q2 error message I tried to display sub-model with only
2011 Feb 04
0
GAM quasipoisson in MuMIn - SOLVED
Hi, Got my issues sorted. Error message solved: I heard from the guy who developed MuMIn and his suggestion worked. "As for the error you get, it seems you are running an old version of MuMIn. Please update the package first." I did (I was only 1 version behind in both R and in MuMIn) and error disappeared! Running quasipoisson GAM in MuMIn: As for my questions on GAM and " to
2010 Aug 25
0
package MuMIn
[cc'ing back to r-help: this is good etiquette so that the responses will be seen by others/ archived for future reference.] On 10-08-25 04:35 PM, Marino Taussig De Bodonia, Agnese wrote: > Yes, I meant "MuMIn" > > the global formula I introduced was: > > rc4.mod<-lm(central$hunting~ central$year + central$gender + central$hunter + central$k.score +
2014 Jun 26
0
AICc in MuMIn package
Hello, I am modelling in glmmADMB count data (I´m using a negative binomial distribution to avoid possitive overdispersion) with four fixed and one random effect. I´m also using MuMIn package to calculate the AICc and also to model averaging using the function dredge. What I do not understand is why dredge calculates a different value of the AICc and degrees of freedom than the function AICc
2011 Sep 20
0
Problems using predict from GAM model averaging (MuMIn)
I am struggling to get GAM model predictions from the top models calculated using model.avg in the package "MuMIn". My model looks something like the following: gamp <- gam(log10(y)~s(x1,bs="tp",k=3)+s(x2,bs="tp",k=3)+ s(x3,bs="tp",k=3)+s(x4,bs="tp",k=3)+s(x5,bs="tp",k=3)+ s(x6,bs="tp",k=3)+x7,data=dat,
2012 Jun 08
2
Consulta sobre GLM-log linear
Estimados amigos, Estoy familiarizándome con los modelos lineales generalizados en R. Estoy interesado en realizar un análisis lig linear y me gustaría saber cuáles son o como extraer los valores correspondientes al chi cuadrado en el análisis para cada grupo y para las interacciones. Desde ya muchas gracias y disculpas si la pregunta es muy básica, adjunto los comandos que estoy utilizando. Si
2012 Jun 08
2
Consulta sobre GLM-log linear
Estimados amigos, Estoy familiarizándome con los modelos lineales generalizados en R. Estoy interesado en realizar un análisis lig linear y me gustaría saber cuáles son o como extraer los valores correspondientes al chi cuadrado en el análisis para cada grupo y para las interacciones. Desde ya muchas gracias y disculpas si la pregunta es muy básica, adjunto los comandos que estoy utilizando. Si
2011 Jul 13
3
Sum weights of independent variables across models (AIC)
Hello, I'd like to sum the weights of each independent variable across linear models that have been evaluated using AIC. For example: > library(MuMIn) > data(Cement) > lm1 <- lm(y ~ ., data = Cement) > dd <- dredge(lm1, beta = TRUE, eval = TRUE, rank = "AICc") > get.models(dd, subset = delta <4) There are 5 models with a Delta AIC Score of
2015 Nov 23
2
Model averaging en R
Hola a todos, He realizado un dredge (para obtener todos los modelos GAM posibles a parir de un full model), luego he seleccionado un confidence set (los modelos que no se diferencian en 2 en AIC) y he hecho un model averaging con ese confidence set. Ahora me gustaría aplicar ese modelo "average" ajustado sobre otro set de datos pero no se como especificar en R que use el mismo modelo
2012 Jun 08
2
Consulta GLM
Estimados amigos, Estoy familiarizándome con los modelos lineales generalizados en R. Estoy interesado en realizar un análisis lig linear y me gustaría saber cuáles son o como extraer los valores correspondientes al chi cuadrado en el análisis para cada grupo y para las interacciones. Desde ya muchas gracias y disculpas si la pregunta es muy básica, adjunto los comandos que estoy utilizando. Si
2013 Nov 27
1
Etimating time to run an analysis?
Hi everyone, I'm new to this list and have searched R help prior for an answer to this question, without luck. If I'm posting in error, please forgive. I'm thinking about using package MuMIn to do multimodel inference with logistic regression. I have many (25) possible predictors and am curious if there is a way to estimate how long the dredge command might take to run? Any
2010 Aug 10
2
question about bayesian model selection for quantile regression
Hi All: Recently I am researching my dissertation about the quantile model selection by bayesian approach. I have the dependent variable(return) and 16 independent variables and I need to select the best variable for each quantile of return. And the method I used is the bayesian approach, which is based on calculating the posterior distibution of model identifier. In other words, I need to obtain
2011 Dec 22
2
Stepwise in lme
I'm manually doing a form of stepwise regression in a mixed model but with many variables, it is time consuming. I thought I'd try to use an automated approach. stepAIC gave me false convergence when I used it with my model, so I thought it can't be hard to set up a basic program to do it based on the p-values. Thus I tried a couple of (very) crude options: 1) trying to
2012 Feb 13
1
Any package for best subset selection on random effects model?
Hi Pros, I know leaps() computes the best subset selection for linear model, and the bestglm() computes the best subset selection for generalized linear model. Is there any package for best subset selection on random effects model, or mixed effects model? Thank you so much. -- View this message in context:
2011 Jun 23
1
Ranking submodels by AIC (more general question)
Here's a more general question following up on the specific question I asked earlier: Can anybody recommend an R command other than mle.aic() (from the wle package) that will give back a ranked list of submodels? It seems like a pretty basic piece of functionality, but the closest I've been able to find is stepAIC(), which as far as I can tell only gives back the best submodel, not a
2013 Apr 16
0
Model ranking (AICc, BIC, QIC) with coxme regression
Hi, I'm actually trying to rank a set of candidate models with an information criterion (AICc, QIC, BIC). The problem I have is that I use mixed-effect cox regression only available with the package {coxme} (see the example below). #Model1 >spring.cox <- coxme (Surv(start, stop, Real_rand) ~ strata(Paired)+R4+R3+R2+(R3|Individual), spring) I've already found some explications in
2010 Aug 22
2
CRAN (and crantastic) updates this week
CRAN (and crantastic) updates this week New packages ------------ * DCGL (1.0) Bao-Hong Liu http://crantastic.org/packages/DCGL Functions for basic differential coexpression analyses: gene filtering, link filtering, DCG (Differentially-Coexpressed Gene) identification and DCL (Differentially-Coexpressed Links) identification.Two algorithms,named DCP and DCe, are
2012 May 03
0
Model Averaging Help
Dear All, I'm using AIC-weighted model averaging to calculate model averaged parameter estimates and partial r-squares of each variable in a 10-variable linear regression. I've been using the MuMIn package to calculate parameter estimates, but am struggling with partial r-squares. There doesn't seem to be any function in the MuMIn package dealing with partial r-square