Fourth quarter 2015 Archives by subject

• Messages sorted by: [ thread ] [ author ] [ date ]
• More info on this list...

Starting: Fri Oct 2 20:53:27 CEST 2015
Ending: Wed Dec 30 21:21:58 CET 2015
Messages: 322

• [R-sig-ME] (1) zero-inflation in glmmADMB; (2) issues with offsets   Laura Farwell
• [R-sig-ME] [R] glmm: random term, overdispersion and comparisons   Ellen Andresen
• [R-sig-ME] [R] glmm: random term, overdispersion and comparisons   Thierry Onkelinx
• [R-sig-ME] about: GLMM for continuous response   Aslıhan Şentürk Acar
• [R-sig-ME] about: GLMM for continuous response   David Winsemius
• [R-sig-ME] about: GLMM for continuous response   David Winsemius
• [R-sig-ME] Advice regarding model choice   Philipp Singer
• [R-sig-ME] Advice regarding model choice   Philipp Singer
• [R-sig-ME] Advise on mixed effect model for a longitudinal study (with lme4)   wphantomfr
• [R-sig-ME] Advise on mixed effect model for a longitudinal study (with lme4)   Thierry Onkelinx
• [R-sig-ME] Advise on mixed effect model for a longitudinal study (with lme4)   wphantomfr
• [R-sig-ME] Advise on mixed effect model for a longitudinal study (with lme4)   Thierry Onkelinx
• [R-sig-ME] An RPubs document on lmer/lmm with 1 M observations   Douglas Bates
• [R-sig-ME] A question about CLMM in R   Georgina Southon
• [R-sig-ME] A question about CLMM in R   Dan McCloy
• [R-sig-ME] A question about CLMM in R   Ben Bolker
• [R-sig-ME] AUTO : No longer at Institut Curie   xavier.paoletti at curie.fr
• [R-sig-ME] AUTO : No longer at Institut Curie   xavier.paoletti at curie.fr
• [R-sig-ME] AUTO : No longer at Institut Curie   xavier.paoletti at curie.fr
• [R-sig-ME] calculation of confidence intervals for random slope model   Henry Travers
• [R-sig-ME] calculation of confidence intervals for random slope model   Ben Bolker
• [R-sig-ME] calculation of confidence intervals for random slope model   Paul Buerkner
• [R-sig-ME] calculation of confidence intervals for random slope model   W. Duncan Wadsworth
• [R-sig-ME] calculation of confidence intervals for random slope model   Ben Bolker
• [R-sig-ME] conditional logistic & weight   knouri
• [R-sig-ME] conditional logistic & weight   Karl Ove Hufthammer
• [R-sig-ME] contrasts among simple effects   James Henson
• [R-sig-ME] contrasts among simple effects   Thierry Onkelinx
• [R-sig-ME] contrasts among simple effects   Lenth, Russell V
• [R-sig-ME] contrasts among simple effects   Thierry Onkelinx
• [R-sig-ME] contrasts among simple effects   James Henson
• [R-sig-ME] contrasts among simple effects   Lenth, Russell V
• [R-sig-ME] Convergence Error: 0 Fixed Correlations and More   Chris Heffner
• [R-sig-ME] correlation of two tests treating items of both tests as random effects?   Jonathan Baron
• [R-sig-ME] correlation of two tests treating items of both tests as random effects?   Jake Westfall
• [R-sig-ME] correlation of two tests treating items of both tests asrandom effects?   David Duffy
• [R-sig-ME] Could we calculate the variance explained by each fixed variable when we use linear mixed model?   黄茹
• [R-sig-ME] Could we calculate the variance explained by each fixed variable when we use linear mixed model?   Dan McCloy
• [R-sig-ME] Could we calculate the variance explained by each fixed variable when we use linear mixed model?   Jake Westfall
• [R-sig-ME] Course: Introduction to GAM and GAMM   Highland Statistics Ltd
• [R-sig-ME] Data structure issue for GLMM models   Anne Blach Overgaard
• [R-sig-ME] Data structure issue for GLMM models   Anne Blach Overgaard
• [R-sig-ME] Data structure issue for GLMM models   Thierry Onkelinx
• [R-sig-ME] different output in R and SAS for GLMM   Adeela Munawar
• [R-sig-ME] different output in R and SAS for GLMM   Ben Bolker
• [R-sig-ME] different output in R and SAS for GLMM   Ben Bolker
• [R-sig-ME] different output in R and SAS for GLMM   Steve Denham
• [R-sig-ME] different output in R and SAS for GLMM   Ben Bolker
• [R-sig-ME] Different within-group error correlation matrices per group   Luis Damiano
• [R-sig-ME] Different within-group error correlation matrices per group   Kevin Wright
• [R-sig-ME] Different within-group error correlation matrices per group   Luis Damiano
• [R-sig-ME] Distribution family for non-negative lower and, upper bound values   Highland Statistics Ltd
• [R-sig-ME] Distribution family for non-negative lower and upper bound values   Gitu wa Mbui
• [R-sig-ME] Distribution family for non-negative lower and upper bound values   Steven J. Pierce
• [R-sig-ME] Distribution family for non-negative lower and upper bound values   Gitu wa Mbui
• [R-sig-ME] Distribution family for non-negative lower and upper bound values   Steven J. Pierce
• [R-sig-ME] error in MCMCglmm (regarding priors)   David Villegas Ríos
• [R-sig-ME] Error messages when running ZIP and ZINB in glmmadmb   Diego Pavon
• [R-sig-ME] fixed effects   Chen, Gang (NIH/NIMH) [C]
• [R-sig-ME] fixed effects   Ben Bolker
• [R-sig-ME] fixed effects   Mitchell Maltenfort
• [R-sig-ME] fixed effects   Ben Bolker
• [R-sig-ME] Fw: question about Type III sums of squares as computed in "CAR'   m51988mnew at juno.com
• [R-sig-ME] Fw: question about Type III sums of squares as computed in "CAR'   Douglas Bates
• [R-sig-ME] Fw: question about Type III sums of squares as computed in "CAR'   m51988mnew at juno.com
• [R-sig-ME] Fw: question about Type III sums of squares as computed in "CAR'   m51988mnew at juno.com
• [R-sig-ME] Fw: question about Type III sums of squares as computed in "CAR'   Fox, John
• [R-sig-ME] Fwd: RE: static vs dynamic factors together?   lmpitombo
• [R-sig-ME] Fwd: Zero cells in contrast matrix problem   Ben Bolker
• [R-sig-ME] gamm4 models memory intensive   Gitu wa Mbui
• [R-sig-ME] gamm4 models memory intensive   Gitu wa Mbui
• [R-sig-ME] GAMM convergence issue with temporal covariate   Hannah L. Linder
• [R-sig-ME] GAMM convergence issue with temporal covariate   Highland Statistics Ltd
• [R-sig-ME] GAMM convergence issue with temporal covariate   Philippi, Tom
• [R-sig-ME] GAMM convergence issue with temporal covariate   Hannah L. Linder
• [R-sig-ME] GLM: Difference between treatment groups for each colony (Tukey posthoc test)   Sophie Waegebaert
• [R-sig-ME] GLM: Difference between treatment groups for each colony (Tukey posthoc test)   paul debes
• [R-sig-ME] GLM: Difference between treatment groups for each colony (Tukey posthoc test)   Sophie Waegebaert
• [R-sig-ME] GLM: Difference between treatment groups for each colony (Tukey posthoc test)   paul debes
• [R-sig-ME] GLM: Difference between treatment groups for each colony (Tukey posthoc test)   Peter Claussen
• [R-sig-ME] glmer: how are “non-integer #successes in a binomial glm!” actually modeled?   Bob Wiley
• [R-sig-ME] glmer: how are “non-integer #successes in a binomial glm!” actually modeled?   Ben Bolker
• [R-sig-ME] glmer: var-cov estimated from RX   Hans Ekbrand
• [R-sig-ME] glmer: var-cov estimated from RX   Ben Bolker
• [R-sig-ME] glmer: var-cov estimated from RX   Hans Ekbrand
• [R-sig-ME] glmer random effects structure: a case   Simone
• [R-sig-ME] glmer random effects structure: a case   Malcolm Fairbrother
• [R-sig-ME] glmer random effects structure: a case   John Morrongiello
• [R-sig-ME] glmer random effects structure: a case   Simone
• [R-sig-ME] glmer random effects structure: a case   Malcolm Fairbrother
• [R-sig-ME] glmer random effects structure: a case   Thierry Onkelinx
• [R-sig-ME] glmer random effects structure: a case   Simone
• [R-sig-ME] glmer random effects structure: a case   Thierry Onkelinx
• [R-sig-ME] glmmADMB   Veronique Dermauw
• [R-sig-ME] glmmADMB   Thierry Onkelinx
• [R-sig-ME] glmmADMB   Veronique Dermauw
• [R-sig-ME] glmmADMB   Thierry Onkelinx
• [R-sig-ME] glmmADMB   Veronique Dermauw
• [R-sig-ME] glmmADMB   Thierry Onkelinx
• [R-sig-ME] glmmADMB   Veronique Dermauw
• [R-sig-ME] glmmADMB   Thierry Onkelinx
• [R-sig-ME] glmmADMB   Veronique Dermauw
• [R-sig-ME] GLMM model failing to converge   Shadiya Al Hashmi
• [R-sig-ME] GLMM model failing to converge   Highland Statistics Ltd
• [R-sig-ME] GLMM model failing to converge   Ben Bolker
• [R-sig-ME] GLMM model failing to converge   Shadiya
• [R-sig-ME] GLMM model failing to converge   Shadiya Al Hashmi
• [R-sig-ME] GLMMs to identify the pure seasonal effect in a repeated measurement   trichter at uni-bremen.de
• [R-sig-ME] GLMMs to identify the pure seasonal effect in a repeated measurement   Thierry Onkelinx
• [R-sig-ME] GLMMs to identify the pure seasonal effect in a repeated measurement   Tim Richter-Heitmann
• [R-sig-ME] GLMMs to identify the pure seasonal effect in a repeated measurement   Thierry Onkelinx
• [R-sig-ME] Hierarchical structure for preservation of observations   Jacob Bukoski
• [R-sig-ME] Hierarchical structure for preservation of observations   Thierry Onkelinx
• [R-sig-ME] Hierarchical structure for preservation of observations   Jacob Bukoski
• [R-sig-ME] How to check the iterative history of convergence and change convergence criterion in glmmadmb   qiujing at udel.edu
• [R-sig-ME] How to check the iterative history of convergence and change convergence criterion in glmmadmb   qiujing2004 at gmail.com
• [R-sig-ME] How to check the iterative history of convergence and change convergence criterion in glmmadmb   Ben Bolker
• [R-sig-ME] How to know if random intercepts and slopes are, necessary for glmer.nb model   Highland Statistics Ltd
• [R-sig-ME] How to know if random intercepts and slopes are, necessary for glmer.nb model   Highland Statistics Ltd
• [R-sig-ME] How to know if random intercepts and slopes are, necessary for glmer.nb model   David Jones
• [R-sig-ME] How to know if random intercepts and slopes are necessary for glmer.nb model   David Jones
• [R-sig-ME] How to know if random intercepts and slopes are necessary for glmer.nb model   Ben Bolker
• [R-sig-ME] how to test interaction correctly   Norman Forschack
• [R-sig-ME] Interaction variance from mcmcglmm   Robert Griffin
• [R-sig-ME] Interaction variance from mcmcglmm   paul debes
• [R-sig-ME] Interaction variance from mcmcglmm   Robert Griffin
• [R-sig-ME] Interaction variance from mcmcglmm   paul debes
• [R-sig-ME] Interpreting posterior mean and effective sample size   Iker Vaquero Alba
• [R-sig-ME] Likelihood Ratio Test for non-nested mixed-effect-model comparison   Francesco Sigona
• [R-sig-ME] Likelihood Ratio Test for non-nested mixed-effect-model comparison   Ben Bolker
• [R-sig-ME] Likelihood Ratio Test for non-nested mixed-effect-model comparison   Merkle, Edgar C.
• [R-sig-ME] Linear mixed model - heterogeneity   Etn bot
• [R-sig-ME] Linear mixed model - heterogeneity   Ben Bolker
• [R-sig-ME] Linear mixed model - heterogeneity   Paul Buerkner
• [R-sig-ME] Linear mixed model - heterogeneity   Etn bot
• [R-sig-ME] Linear mixed model - heterogeneity   Etn bot
• [R-sig-ME] Linear mixed model - heterogeneity   Ben Bolker
• [R-sig-ME] Linear mixed model - heterogeneity   Etn bot
• [R-sig-ME] Linear mixed model - heterogeneity (Etn bot)   Highland Statistics Ltd
• [R-sig-ME] Linear mixed model - heterogeneity (Etn bot)   Etn bot
• [R-sig-ME] lme4 glmer convergence question   Sally A. Roman
• [R-sig-ME] lme4 glmer convergence question   Ben Bolker
• [R-sig-ME] lmer model construction   Jeremy Chacon
• [R-sig-ME] lmer model construction   Thierry Onkelinx
• [R-sig-ME] lmer model construction   Jeremy Chacon
• [R-sig-ME] lmer model construction   Thierry Onkelinx
• [R-sig-ME] lmer model construction   Jake Westfall
• [R-sig-ME] lmer model construction   Jeremy Chacon
• [R-sig-ME] lmer nonconvergent: care to run and explain?   Paul Johnson
• [R-sig-ME] lmer nonconvergent: care to run and explain?   David Duffy
• [R-sig-ME] lmer nonconvergent: care to run and explain?   Paul Johnson
• [R-sig-ME] lmer nonconvergent: care to run and explain?   Thierry Onkelinx
• [R-sig-ME] lmer nonconvergent: care to run and explain?   Douglas Bates
• [R-sig-ME] lmer nonconvergent: care to run and explain?   Douglas Bates
• [R-sig-ME] lmer nonconvergent: care to run and explain?   Douglas Bates
• [R-sig-ME] lmer nonconvergent: care to run and explain?   Paul Johnson
• [R-sig-ME] lmer nonconvergent: care to run and explain?   Douglas Bates
• [R-sig-ME] LMM diagnostics: conditional residuals correlated highly with fitted values   Yizhou Ma
• [R-sig-ME] LMM diagnostics: conditional residuals correlated highly with fitted values   Thierry Onkelinx
• [R-sig-ME] LMM diagnostics: conditional residuals correlated highly with fitted values   Yizhou Ma
• [R-sig-ME] LMM diagnostics: conditional residuals correlated highly with fitted values   Thierry Onkelinx
• [R-sig-ME] LMM diagnostics: conditional residuals correlated highly with fitted values   Yizhou Ma
• [R-sig-ME] LMM diagnostics: conditional residuals correlated highly with fitted values   Thierry Onkelinx
• [R-sig-ME] LMM diagnostics: conditional residuals correlated highly with fitted values   Yizhou Ma
• [R-sig-ME] LMM diagnostics: conditional residuals correlated highly with fitted values   Ulf Köther
• [R-sig-ME] logistic regression with glmer, three ways   Malcolm Fairbrother
• [R-sig-ME] logistic regression with glmer, three ways   David Duffy
• [R-sig-ME] logistic regression with glmer, three ways   Malcolm Fairbrother
• [R-sig-ME] main effect significance disappears when interaction is modeled   Thierry Onkelinx
• [R-sig-ME] main effect significance disappears when interaction is modeled   Francesco Sigona
• [R-sig-ME] MCMCglmm: Correct prior?   Katrijn Delaruelle
• [R-sig-ME] MCMCglmm: Question about posterior mean.   Iker Vaquero Alba
• [R-sig-ME] MCMCglmm diagnostics   Iker Vaquero Alba
• [R-sig-ME] MCMCglmm diagnostics   Jarrod Hadfield
• [R-sig-ME] MCMCglmm diagnostics   Iker Vaquero Alba
• [R-sig-ME] MCMCglmm error-in-variables (total least squares) model?   Alberto Gallano
• [R-sig-ME] MCMCglmm prior specification   Iker Vaquero Alba
• [R-sig-ME] MCMCglmm prior specification   Jarrod Hadfield
• [R-sig-ME] MCMCglmm prior specification   Iker Vaquero Alba
• [R-sig-ME] MCMCglmm prior specification   Jarrod Hadfield
• [R-sig-ME] MCMCglmm prior specification   Iker Vaquero Alba
• [R-sig-ME] MCMCglmm update   Jarrod Hadfield
• [R-sig-ME] MCMCglmm update   Jarrod Hadfield
• [R-sig-ME] mixed effects model proportion data that are not 0 and 1's   M West
• [R-sig-ME] mixed effects model proportion data that are not 0 and 1's   John Sorkin
• [R-sig-ME] mixed effects model proportion data that are not 0 and 1's   Ben Bolker
• [R-sig-ME] mixed effects model proportion data that are not 0 and 1's   M West
• [R-sig-ME] mixed effects model proportion data that are not 0 and 1's   M West
• [R-sig-ME] Mixed modelling and Species Area Relationship (SAR)   Gitu wa Mbui
• [R-sig-ME] Mixed modelling and Species Area Relationship (SAR)   Thierry Onkelinx
• [R-sig-ME] Mixed modelling and Species Area Relationship (SAR)   Ben Bolker
• [R-sig-ME] Mixed modelling and Species Area Relationship (SAR)   Gitu wa Mbui
• [R-sig-ME] Mixed modelling course, Lisbon, Portugal   Highland Statistics Ltd
• [R-sig-ME] Mixed model predictions using sim   Tom Wilding
• [R-sig-ME] Mixed model predictions using sim   Vincent Dorie
• [R-sig-ME] Mixed model predictions using sim   Tom Wilding
• [R-sig-ME] mixed probit and rare events (MCMCglmm)   Linus Holtermann
• [R-sig-ME] model building   Davide Guido
• [R-sig-ME] model building   Thierry Onkelinx
• [R-sig-ME] modeling the effect of grass height on insect biomass   Joaquín Aldabe
• [R-sig-ME] modeling the effect of grass height on insect biomass   Thierry Onkelinx
• [R-sig-ME] modeling the effect of grass height on insect biomass   Thierry Onkelinx
• [R-sig-ME] modeling the effect of grass height on insect biomass   Joaquín Aldabe
• [R-sig-ME] Model is nearly unidentifiable with lmer   Chunyun Ma
• [R-sig-ME] Model is nearly unidentifiable with lmer   Ben Bolker
• [R-sig-ME] Model is nearly unidentifiable with lmer   Alex Fine
• [R-sig-ME] Model is nearly unidentifiable with lmer   Ben Bolker
• [R-sig-ME] Model is nearly unidentifiable with lmer   Chunyun Ma
• [R-sig-ME] Model is nearly unidentifiable with lmer   Chunyun Ma
• [R-sig-ME] Model is nearly unidentifiable with lmer   Ben Bolker
• [R-sig-ME] Model is nearly unidentifiable with lmer   Ben Bolker
• [R-sig-ME] model selection in MCMCglmm   David Villegas Ríos
• [R-sig-ME] Model Validation with glmmADMB   Mondain-Monval, Thomas
• [R-sig-ME] Model with no random intercept?   Salmon, Maëlle
• [R-sig-ME] Model with no random intercept?   Philipp Singer
• [R-sig-ME] Model with no random intercept?   Ben Bolker
• [R-sig-ME] multiple random effects and correlation structure in nlme   Karl Jarvis
• [R-sig-ME] multiple random effects and correlation structure in nlme   Thierry Onkelinx
• [R-sig-ME] multiple random effects and correlation structure in nlme   Karl Jarvis
• [R-sig-ME] Orthogonal Polynomial contrasts with ordered factors   Quentin Schorpp
• [R-sig-ME] Orthogonal Polynomial contrasts with ordered factors   Steve Denham
• [R-sig-ME] Orthogonal Polynomial contrasts with ordered factors   Quentin Schorpp
• [R-sig-ME] Orthogonal Polynomial contrasts with ordered factors   Steve Denham
• [R-sig-ME] please remove my email from this list   Alejandro Martínez Abraín
• [R-sig-ME] Plotting a glmmADMB model   Luiz Ernesto Costa Schmidt
• [R-sig-ME] Plotting predicted values mcmcglmm   Lotte van Boheemen
• [R-sig-ME] Plotting predicted values mcmcglmm   Lotte van Boheemen
• [R-sig-ME] Plotting predicted values mcmcglmm   romunov
• [R-sig-ME] Posterior covariance matrix of fixed effects from MCMCglmm?   Mikhail Matz
• [R-sig-ME] Posterior covariance matrix of fixed effects from MCMCglmm?   Ben Bolker
• [R-sig-ME] Posterior covariance matrix of fixed effects from MCMCglmm?   Ben Bolker
• [R-sig-ME] Print out of function lmer   li li
• [R-sig-ME] Print out of function lmer   Ben Bolker
• [R-sig-ME] Print out of function lmer   Ben Bolker
• [R-sig-ME] priors for fixed-effect covariates using bglmer - centering the t-distribution?   James Rudge
• [R-sig-ME] priors for fixed-effect covariates using bglmer - centering the t-distribution?   Vincent Dorie
• [R-sig-ME] priors for fixed-effect covariates using bglmer - centering the t-distribution?   James Rudge
• [R-sig-ME] Problems with model (assumptions)   Philipp Singer
• [R-sig-ME] Problems with model (assumptions)   Thierry Onkelinx
• [R-sig-ME] Problems with model (assumptions)   Ben Bolker
• [R-sig-ME] Problems with model (assumptions)   Philipp Singer
• [R-sig-ME] Problems with model (assumptions)   Ben Bolker
• [R-sig-ME] Problems with model (assumptions)   Philipp Singer
• [R-sig-ME] Proportion data: calculation of significance difference in infection rate   Sophie Waegebaert
• [R-sig-ME] Question about lme4   jesse cloud
• [R-sig-ME] question about Type III sums of squares as computed in "CAR'   m51988mnew at juno.com
• [R-sig-ME] question about Type III sums of squares as computed in "CAR'   Phillip Alday
• [R-sig-ME] Question on random effects glm interpretation   Emmanuel Curis
• [R-sig-ME] Question on random effects glm interpretation   Thierry Onkelinx
• [R-sig-ME] Question on random effects glm interpretation   Emmanuel Curis
• [R-sig-ME] Question on random effects glm interpretation   Thierry Onkelinx
• [R-sig-ME] Question on random effects glm interpretation   Ben Bolker
• [R-sig-ME] Question on random effects glm interpretation   Emmanuel Curis
• [R-sig-ME] Question on random effects glm interpretation   Ben Bolker
• [R-sig-ME] Question on random effects glm interpretation   David Duffy
• [R-sig-ME] Question on random effects glm interpretation   Emmanuel Curis
• [R-sig-ME] Question on random effects glm interpretation   Emmanuel Curis
• [R-sig-ME] questions on glmmADMB package   Marcin Przystalski
• [R-sig-ME] questions on glmmADMB package   dave fournier
• [R-sig-ME] Question to lme4: Higher Level Response   Douglas Bates
• [R-sig-ME] Question to lme4: Higher Level Response   Jake Westfall
• [R-sig-ME] Question to lme4: Higher Level Response   Steven J. Pierce
• [R-sig-ME] random effect model   li li
• [R-sig-ME] random effect model   Ben Bolker
• [R-sig-ME] Random effects correlations and factor reference levels   Christopher Knight
• [R-sig-ME] Random effects correlations and factor reference levels   paul debes
• [R-sig-ME] Random effects correlations and factor reference levels   Christopher Knight
• [R-sig-ME] Random intercept and slope after model Averaging   REHAN UL HAQ
• [R-sig-ME] Random vs. fixed effects   Shadiya Al Hashmi
• [R-sig-ME] Random vs. fixed effects   Thierry Onkelinx
• [R-sig-ME] Random vs. fixed effects   Shadiya Al Hashmi
• [R-sig-ME] Random vs. fixed effects   Highland Statistics Ltd
• [R-sig-ME] Random vs. fixed effects   Thierry Onkelinx
• [R-sig-ME] Reserved variable "trait"   Iker Vaquero Alba
• [R-sig-ME] residual covariance structure and long format data in MCMCglmm   David Villegas Ríos
• [R-sig-ME] residual covariance structure and long format data in MCMCglmm   Jarrod Hadfield
• [R-sig-ME] residual covariance structure and long format data in MCMCglmm   David Villegas Ríos
• [R-sig-ME] residual covariance structure and long format data in MCMCglmm   Jarrod Hadfield
• [R-sig-ME] Selecting a subset of data for binary mixed model   Kanix Wang
• [R-sig-ME] Simulating Data from a Linear Mixed Model   Hintz, F. (Florian)
• [R-sig-ME] Simulating Data from a Linear Mixed Model   Ben Bolker
• [R-sig-ME] Simulating Data from a Linear Mixed Model   Douglas Bates
• [R-sig-ME] Simulating Data from a Linear Mixed Model   Perry de Valpine
• [R-sig-ME] Simulating Data from a Linear Mixed Model   Ben Bolker
• [R-sig-ME] Small sample Size; repeated measurements binomial glmer   Quentin Schorpp
• [R-sig-ME] Small sample Size; repeated measurements binomial glmer   Ben Bolker
• [R-sig-ME] Small sample Size; repeated measurements binomial glmer   Quentin Schorpp
• [R-sig-ME] Standard errors of group-wise random effect intercepts   Jacob Bukoski
• [R-sig-ME] Standard errors of group-wise random effect intercepts   Thierry Onkelinx
• [R-sig-ME] Standard errors of group-wise random effect intercepts   Jacob Bukoski
• [R-sig-ME] Testing overdispersion Gamma glmer   Sophie Waegebaert
• [R-sig-ME] Testing overdispersion Gamma glmer   Highland Statistics Ltd
• [R-sig-ME] Time as both fixed and random term   Lionel
• [R-sig-ME] Time as both fixed and random term   shi_peijian
• [R-sig-ME] Time as both fixed and random term   Pantelis Hadjipantelis
• [R-sig-ME] Time as both fixed and random term   paul debes
• [R-sig-ME] Time as both fixed and random term   Lionel
• [R-sig-ME] treating measurement occasions as a numerical or as a factor predictor   K Imran M
• [R-sig-ME] treating measurement occasions as a numerical or as a factor predictor   Rich Shepard
• [R-sig-ME] treating measurement occasions as a numerical or as a factor predictor   Ben Bolker
• [R-sig-ME] treating measurement occasions as a numerical or as a factor predictor   K Imran M
• [R-sig-ME] Understanding different (residual) output for glmer.nb vs glmmPQL   Philipp Singer
• [R-sig-ME] Vignettes RePsychLing   lorenz.gygax at agroscope.admin.ch
• [R-sig-ME] Vignettes RePsychLing   Hadley Wickham
• [R-sig-ME] Vignettes RePsychLing   lorenz.gygax at agroscope.admin.ch
• [R-sig-ME] Warning message   katrin.luder at iee.unibe.ch
• [R-sig-ME] Warning message   Ben Bolker
• [R-sig-ME] zero-inflation in glmmADMB   Highland Statistics Ltd
• [R-sig-ME] Zero cells in contrast matrix problem   Francesco Romano
• [R-sig-ME] Zero cells in contrast matrix problem   Ben Bolker
• [R-sig-ME] Zero cells in contrast matrix problem   Francesco Romano
• [R-sig-ME] Zero cells in contrast matrix problem   Ben Bolker
• [R-sig-ME] Zero cells in contrast matrix problem   Francesco Romano
• [R-sig-ME] Zero cells in contrast matrix problem   Ben Bolker
• [R-sig-ME] Zero cells in contrast matrix problem   Ben Bolker
• [R-sig-ME] Zero cells in contrast matrix problem   Francesco Romano
• [R-sig-ME] Zero cells in contrast matrix problem   Thompson,Paul
• [R-sig-ME] Zero cells in contrast matrix problem   Ben Bolker
• [R-sig-ME] Zero cells in contrast matrix problem   Ben Bolker
• [R-sig-ME] zero inflated mixed models   Simone Bianchi
• [R-sig-ME] zero inflated mixed models   Mollie Brooks
• [R-sig-ME] zero inflated mixed models   David Duffy

Last message date: Wed Dec 30 21:21:58 CET 2015
Archived on: Fri Jan 1 17:59:15 CET 2016

• Messages sorted by: [ thread ] [ author ] [ date ]
• More info on this list...