Fourth quarter 2014 Archives by subject

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Starting: Wed Oct 1 01:47:00 CEST 2014
Ending: Mon Dec 29 06:53:53 CET 2014
Messages: 335

• [R-sig-ME] "Multilevel Modeling Using R" and variance estimates   Douglas Bates
• [R-sig-ME] "Multilevel Modeling Using R" and variance estimates   Marko Bachl
• [R-sig-ME] "Multilevel Modeling Using R" and variance estimates   Ben Bolker
• [R-sig-ME] "Multilevel Modeling Using R" and variance estimates   Douglas Bates
• [R-sig-ME] (no subject)   Emily L. De Stigter
• [R-sig-ME] (no subject)   ONKELINX, Thierry
• [R-sig-ME] (no subject)   John Maindonald
• [R-sig-ME] 8 statistics course; January - June 2015   Highland Statistics Ltd
• [R-sig-ME] [Lme4-authors] Mixed effect models with user-defined links in R   lme4 maintainer
• [R-sig-ME] [R] nlme package: changing reference for varIdent parameter estimates in summary.gls   ONKELINX, Thierry
• [R-sig-ME] Advice   Julie Webbs
• [R-sig-ME] Announcing new version of afex (0.11-131)   Henrik Singmann
• [R-sig-ME] anova (lm, lmer ) question   Ben Pelzer
• [R-sig-ME] anova (lm, lmer ) question   romunov
• [R-sig-ME] anova (lm, lmer ) question   Ben Bolker
• [R-sig-ME] anova (lm, lmer ) question   Ken Beath
• [R-sig-ME] anova (lm, lmer ) question   Ben Bolker
• [R-sig-ME] anova (lm, lmer ) question   Ben Pelzer
• [R-sig-ME] anova (lm, lmer ) question   Ben Bolker
• [R-sig-ME] anova (lm, lmer ) question   Farrar, David
• [R-sig-ME] anova (lm, lmer ) question   Ben Bolker
• [R-sig-ME] anova (lm, lmer ) question   Farrar, David
• [R-sig-ME] ANOVA for large data sets   Aneta
• [R-sig-ME] ANOVA for large data sets   Ben Bolker
• [R-sig-ME] Approximation to Marginal Likelihood of GLMM in lme4‏   Lee Yan Liang
• [R-sig-ME] Approximation to Marginal Likelihood of GLMM in lme4‏   Ken Beath
• [R-sig-ME] Bayesian hypothesis testing using MCMCglmm   Alberto Gallano
• [R-sig-ME] Binomial model R^2 and ICC calculation with lme4   Maurits Van Zinnicq Bergmann
• [R-sig-ME] Binomial model R^2 and ICC calculation with lme4   Paul Johnson
• [R-sig-ME] Binomial model variance and repeatability estimates with MCMCglmm   Ned Dochtermann
• [R-sig-ME] Binomial model variance and repeatability estimates with MCMCglmm   Jarrod Hadfield
• [R-sig-ME] Binomial model variance and repeatability estimates with MCMCglmm   Ned Dochtermann
• [R-sig-ME] Binomial model variance and repeatability estimates with MCMCglmm   Jarrod Hadfield
• [R-sig-ME] Bivariate (or multivariate) model in MCMCglmm   Napoleon Vargas
• [R-sig-ME] comparing posterior means   Ben Pelzer
• [R-sig-ME] comparing posterior means   Emmanuel Curis
• [R-sig-ME] comparing posterior means   Doran, Harold
• [R-sig-ME] comparing posterior means   Douglas Bates
• [R-sig-ME] comparing posterior means   Doran, Harold
• [R-sig-ME] comparing posterior means   Douglas Bates
• [R-sig-ME] comparing posterior means   Ben Pelzer
• [R-sig-ME] comparing posterior means   Jake Westfall
• [R-sig-ME] confidence intervals for random slopes   Ben Bolker
• [R-sig-ME] Convergence warnings in lme4   adam.hayward at ed.ac.uk
• [R-sig-ME] Convergence warnings in lme4   Ben Bolker
• [R-sig-ME] correlation of random factors in mixed models   Luis Cayuela Delgado
• [R-sig-ME] correlation of random factors in mixed models   Ken Beath
• [R-sig-ME] Crossed and nested factors in experimental designs: Are there any flowcharts for decision making?   Mehdi Abedi
• [R-sig-ME] Crossed and nested factors in experimental designs: Are there any flowcharts for decision making?   Ben Bolker
• [R-sig-ME] Crossed and nested factors in experimental designs: Are there any flowcharts for decision making?   Mehdi Abedi
• [R-sig-ME] Crossed and nested factors in experimental designs: Are there any flowcharts for decision making?   Jaime Ashander
• [R-sig-ME] Crossed and nested factors in experimental designs: Are there any flowcharts for decision making?   Jake Westfall
• [R-sig-ME] Crossed and nested factors in experimental designs: Are there any flowcharts for decision making?   Mehdi Abedi
• [R-sig-ME] default optimizer in lmer 1.1-7?   Ben Bolker
• [R-sig-ME] DIC with multiple MCMCglmm chains   Daniel Anderson
• [R-sig-ME] Effect size for lmer and glmer   Hamada Elsayed Ali
• [R-sig-ME] Effect size for lmer and glmer   Highland Statistics Ltd
• [R-sig-ME] Error in predict a linear mixed model with predict   m.tasallizadeh
• [R-sig-ME] Error message   Luciano La Sala
• [R-sig-ME] Error message   Daniel Wright
• [R-sig-ME] Error message   Ben Bolker
• [R-sig-ME] Error message   Luciano La Sala
• [R-sig-ME] Error message   Ben Bolker
• [R-sig-ME] Error message   Ken Beath
• [R-sig-ME] Error message   Ben Bolker
• [R-sig-ME] Error message   Ken Beath
• [R-sig-ME] error message using glmmADMB   Nagata Mizuho
• [R-sig-ME] error when looping many MCMCglmm runs   Manabu Sakamoto
• [R-sig-ME] error when looping many MCMCglmm runs   Jarrod Hadfield
• [R-sig-ME] Estimating/fixing covariances in multi-response model with several zero-inflated variables?   Adrian Jaeggi
• [R-sig-ME] Estimating/fixing covariances in multi-response model with several zero-inflated variables?   ONKELINX, Thierry
• [R-sig-ME] Estimating/fixing covariances in multi-response model with several zero-inflated variables?   Jarrod Hadfield
• [R-sig-ME] Estimating indirect contributions in a mixed-treatment comparison (a.k.a. network meta-analysis)   Jouve, Thomas
• [R-sig-ME] Estimation Methods in lme4   Mohd Masood
• [R-sig-ME] Estimation Methods in lme4   Ben Bolker
• [R-sig-ME] Extracting weights from an lme object   robert bagchi
• [R-sig-ME] Extracting weights from an lme object   Ben Bolker
• [R-sig-ME] Extracting weights from an lme object   robert bagchi
• [R-sig-ME] Extract standard error of the variance component in lme4 package (GLMM).   Martí Casals
• [R-sig-ME] Extract standard error of the variance component in lme4 package (GLMM).   Steve Walker
• [R-sig-ME] Extract standard error of the variance component in lme4 package (GLMM).   Ben Bolker
• [R-sig-ME] Extract standard error of the variance component in lme4 package (GLMM).   Martí Casals
• [R-sig-ME] Extract standard error of the variance component in lme4 package (GLMM).   Ben Bolker
• [R-sig-ME] Fixing phylogenetic heritability in MCMCglmm   Manabu Sakamoto
• [R-sig-ME] Fixing phylogenetic heritability in MCMCglmm   Jarrod Hadfield
• [R-sig-ME] Follow up question testing three way interaction between two fixed effects and a random effect nested in a fixed   Eoin Duffy
• [R-sig-ME] Follow up question testing three way interaction between two fixed effects and a random effect nested in a fixed   ONKELINX, Thierry
• [R-sig-ME] Formula Explanation in lme4 Vignette   Dario Strbenac
• [R-sig-ME] Formula Explanation in lme4 Vignette   Emmanuel Curis
• [R-sig-ME] From: Tina Wey   Tina Wey
• [R-sig-ME] from: Tina Wey   Tina Wey
• [R-sig-ME] Fw: lme4   Ebi Safaie
• [R-sig-ME] Fw: lme4   Ben Bolker
• [R-sig-ME] Fwd: [Lme4-authors] LME4 and Lmer model   Ken Beath
• [R-sig-ME] Fwd: [Lme4-authors] LME4 and Lmer model   Zhanyou Xu
• [R-sig-ME] Fwd: [Lme4-authors] LME4 and Lmer model   Ben Bolker
• [R-sig-ME] Fwd: lme4 heteroscedasticity???   Highland Statistics Ltd
• [R-sig-ME] Fwd: lme4 Question   Ben Bolker
• [R-sig-ME] Fwd: Re: ANOVA for large data sets   Ben Bolker
• [R-sig-ME] gamm4: predict to reflect random effects?   Mark Miller
• [R-sig-ME] gamm4: predict to reflect random effects?   Mollie Brooks
• [R-sig-ME] gamm4: predict to reflect random effects?   Mark Miller
• [R-sig-ME] GLMM's with quadrature   Boylan, Ross
• [R-sig-ME] GLMM's with quadrature   Ben Bolker
• [R-sig-ME] GLMM's with quadrature   Boylan, Ross
• [R-sig-ME] GLMM's with quadrature   Ben Bolker
• [R-sig-ME] GLMM's with quadrature   Boylan, Ross
• [R-sig-ME] GLMM's with quadrature   Ben Bolker
• [R-sig-ME] glmmADMB: "Error in Z * sweep"   Stratford, Jeffrey
• [R-sig-ME] glmmADMB error messages with percentage cover data   Elwyn Sharps
• [R-sig-ME] glmmADMB error messages with percentage cover data (Elwyn Sharps)   Highland Statistics Ltd
• [R-sig-ME] glmmADMB error messages with percentage cover data (Elwyn Sharps)   Elwyn Sharps
• [R-sig-ME] glmmADMB error messages with percentage cover data (Elwyn Sharps)   Ben Bolker
• [R-sig-ME] glmmADMB error messages with percentage cover data (Elwyn Sharps)   Ben Bolker
• [R-sig-ME] glmmadmb function   Ben Bolker
• [R-sig-ME] glmmadmb random effects help   Hacker, Greg (CDPH-CID-DCDC)
• [R-sig-ME] glmmadmb random effects help   ONKELINX, Thierry
• [R-sig-ME] glmmadmb random effects help   ONKELINX, Thierry
• [R-sig-ME] Help request - MCMCglmm model with repeat measures and phylogenetic component   Tricia Markle
• [R-sig-ME] Help with mosaic plot   Francesco Romano
• [R-sig-ME] How do I interpret linear mixed model contrast estimates from multcomp::glht()?   Matthew Van Scoyoc
• [R-sig-ME] How do I interpret linear mixed model contrast estimates from multcomp::glht()?   ONKELINX, Thierry
• [R-sig-ME] How do I interpret linear mixed model contrast estimates from multcomp::glht()?   Matthew Van Scoyoc
• [R-sig-ME] How do I interpret linear mixed model contrast estimates from multcomp::glht()?   Ken Beath
• [R-sig-ME] How do I interpret linear mixed model contrast estimates from multcomp::glht()?   Matthew Van Scoyoc
• [R-sig-ME] How do I interpret linear mixed model contrast estimates from multcomp::glht()?   ONKELINX, Thierry
• [R-sig-ME] How do I interpret linear mixed model contrast estimates from multcomp::glht()?   Lenth, Russell V
• [R-sig-ME] How to calculate the level-1 variance of a GLMM (Poisson or Additive Over-dispersed Poisson) model?   Graham B. McNamara
• [R-sig-ME] How to calculate the level-1 variance of a GLMM (Poisson or Additive Over-dispersed Poisson) model?   Ulf Köther
• [R-sig-ME] interpretation of categorical crossed effect in lme4   Andrew McAleavey
• [R-sig-ME] interpretation of categorical crossed effect in lme4   Ken Beath
• [R-sig-ME] interpretation of categorical crossed effect in lme4   Andrew McAleavey
• [R-sig-ME] interpretation of categorical crossed effect in lme4   Ken Beath
• [R-sig-ME] interpretation of covariate effect on traits in multinomial mixed model (MCMCglmm)   Dominique CARVAL
• [R-sig-ME] interpretation of range value from lme model with exponential correlation structure   Janee Wilkinson
• [R-sig-ME] interpretation of range value from lme model with exponential correlation structure   Kevin Wright
• [R-sig-ME] interpretation variance-covariance estimates with gaussian and censored exponential   Van Dongen Stefan
• [R-sig-ME] interpretation variance-covariance estimates with gaussian and censored exponential   Jarrod Hadfield
• [R-sig-ME] Julia vs nlme vs lme4 implementation of fitting linear mixed models   W Robert Long
• [R-sig-ME] Julia vs nlme vs lme4 implementation of fitting linear mixed models   Phillip Alday
• [R-sig-ME] Julia vs nlme vs lme4 implementation of fitting linear mixed models   W Robert Long
• [R-sig-ME] Julia vs nlme vs lme4 implementation of fitting linear mixed models   Phillip Alday
• [R-sig-ME] Julia vs nlme vs lme4 implementation of fitting linear mixed models   W Robert Long
• [R-sig-ME] Julia vs nlme vs lme4 implementation of fitting linear mixed models   Douglas Bates
• [R-sig-ME] Julia vs nlme vs lme4 implementation of fitting linear mixed models   W Robert Long
• [R-sig-ME] lme4   Safaie, Ebrahim
• [R-sig-ME] lme4   Ben Bolker
• [R-sig-ME] lme4   Ben Bolker
• [R-sig-ME] lme4 (your singularity check with getME())   Ben Bolker
• [R-sig-ME] lme4 heteroscedasticity???   Douglas Bates
• [R-sig-ME] lme4 heteroscedasticity???   Paul Johnson
• [R-sig-ME] lme4 heteroscedasticity???   Douglas Bates
• [R-sig-ME] lme4 heteroscedasticity???   Paul Johnson
• [R-sig-ME] lme4 heteroscedasticity???   Ben Bolker
• [R-sig-ME] lme4 Question   Ben Bolker
• [R-sig-ME] lme4 troubles   Ben Bolker
• [R-sig-ME] lme4 troubles   Andrew C. Shaver
• [R-sig-ME] lmer model converged before, but couldn't now   Zhaohong Wu
• [R-sig-ME] lmer model converged before, but couldn't now   Ben Bolker
• [R-sig-ME] lmertest F-test anova(fullm) and anova(fullm,reducedm)   marie devaine
• [R-sig-ME] lmertest F-test anova(fullm) and anova(fullm, reducedm)   Lionel
• [R-sig-ME] lmertest F-test anova(fullm) and anova(fullm, reducedm)   marie devaine
• [R-sig-ME] lmertest F-test anova(fullm) and anova(fullm, reducedm)   Lionel
• [R-sig-ME] lme with a known correlation matrix for the random effects   Mitov Venelin
• [R-sig-ME] lme with a known correlation matrix for the random effects   ONKELINX, Thierry
• [R-sig-ME] lme with a known correlation matrix for the random effects   Viechtbauer Wolfgang (STAT)
• [R-sig-ME] lme with a known correlation matrix for the random effects   Vmitov at gmail.com
• [R-sig-ME] lme with a known correlation matrix for the random effects   Vmitov at gmail.com
• [R-sig-ME] Longitudinal Model   Leonardo Bergamini
• [R-sig-ME] Longitudinal Model   ONKELINX, Thierry
• [R-sig-ME] MCMC fitting in glmmADMB   maren
• [R-sig-ME] MCMC fitting in glmmADMB   Ben Bolker
• [R-sig-ME] MCMC fitting in glmmADMB   maren
• [R-sig-ME] MCMC fitting in glmmADMB   - -
• [R-sig-ME] MCMCglmm   Tanya Pennell
• [R-sig-ME] MCMCglmm Heterogenous Residual Variance in a Categorial Model   FERNANDEZ Ana maria
• [R-sig-ME] MCMCglmm Heterogenous Residual Variance in a Categorial Model   Jarrod Hadfield
• [R-sig-ME] MCMCglmm prior distributions   Boby Mathew
• [R-sig-ME] MCMCglmm prior distributions   Jarrod Hadfield
• [R-sig-ME] MCMCglmm prior distributions   Boby Mathew
• [R-sig-ME] MCMCglmm prior distributions   Jarrod Hadfield
• [R-sig-ME] MCMCglmm prior distributions   Boby Mathew
• [R-sig-ME] MCMCglmm prior distributions   Jarrod Hadfield
• [R-sig-ME] MCMCglmm prior distributions   Boby Mathew
• [R-sig-ME] MCMCglmm prior distributions   Jarrod Hadfield
• [R-sig-ME] MCMCglmm prior distributions   Boby Mathew
• [R-sig-ME] MCMCglmm priors and random effects for phylogenetic mixed model   Alberto Gallano
• [R-sig-ME] MCMCglmm priors and random effects for phylogenetic mixed model   Jarrod Hadfield
• [R-sig-ME] MCMCglmm user defined incidence matrix   Boby Mathew
• [R-sig-ME] MCMCglmm user defined incidence matrix   Jarrod Hadfield
• [R-sig-ME] Meta-analysis for heritability using MCMCglmm?   Jackie Wood
• [R-sig-ME] Meta-analysis for heritability using MCMCglmm?   Ken Beath
• [R-sig-ME] Meta-analysis for heritability using MCMCglmm?   Jarrod Hadfield
• [R-sig-ME] mixed zero-inflated Poisson regression model   Dieter Anseeuw
• [R-sig-ME] mixed zero-inflated Poisson regression model   ONKELINX, Thierry
• [R-sig-ME] mixed zero-inflated Poisson regression model (Dieter Anseeuw)   Highland Statistics Ltd
• [R-sig-ME] MLM / HLM diagnostics   Alex Whitworth
• [R-sig-ME] MLM / HLM diagnostics   Marko Bachl
• [R-sig-ME] MLM / HLM diagnostics   Steven J. Pierce
• [R-sig-ME] Model comparisons   Yasuaki SHINOHARA
• [R-sig-ME] Model comparisons   ONKELINX, Thierry
• [R-sig-ME] Model comparisons   Yasuaki SHINOHARA
• [R-sig-ME] Model comparisons   ONKELINX, Thierry
• [R-sig-ME] Model comparisons   Yasuaki SHINOHARA
• [R-sig-ME] Model correlated responses in interval-censored data   Jason Paul
• [R-sig-ME] Modeling variance heterogeneity in lme4 + meaning of VarCorr values   Emmanuel Curis
• [R-sig-ME] Modeling variance heterogeneity in lme4 + meaning of VarCorr values   ONKELINX, Thierry
• [R-sig-ME] Modeling variance heterogeneity in lme4 + meaning of VarCorr values   Emmanuel Curis
• [R-sig-ME] Modeling variance heterogeneity in lme4 + meaning of VarCorr values   ONKELINX, Thierry
• [R-sig-ME] Model selection GLM vs. GLMMs   Nelida Villaseñor
• [R-sig-ME] Model selection GLM vs. GLMMs   Ben Bolker
• [R-sig-ME] Model selection GLM vs. GLMMs   Ben Bolker
• [R-sig-ME] Model selection GLM vs. GLMMs   Douglas Bates
• [R-sig-ME] Multiple comparison correction?   Ahnate Lim
• [R-sig-ME] Multiple comparison correction?   Malcolm Fairbrother
• [R-sig-ME] Multiple comparison correction?   Lenth, Russell V
• [R-sig-ME] Multiple comparison correction?   Daniel Wright
• [R-sig-ME] Multiple comparison correction?   Ahnate Lim
• [R-sig-ME] Multiple comparisons with interaction   Mayara Amescua
• [R-sig-ME] Multiple comparisons with interaction   ONKELINX, Thierry
• [R-sig-ME] Multiple post hoc comparisons in MCMCglmm   Eric Michel
• [R-sig-ME] Multivariate analysis for proportional data   Mayara Amescua
• [R-sig-ME] Multivariate analysis for proportional data   Ben Bolker
• [R-sig-ME] Multivariate analysis for proportional data   Rich Shepard
• [R-sig-ME] Multivariate analysis for proportional data   Rolf Turner
• [R-sig-ME] Need help with Random Effect specification: nested Random Effects and a_priori known regimes (MCMCglmm)   Linus Holtermann
• [R-sig-ME] Need help with Random Effect specification: nested Random Effects and a_priori known regimes (MCMCglmm)   Jarrod Hadfield
• [R-sig-ME] Need help with Random Effect specification: nested Random Effects and a_priori known regimes (MCMCglmm)   Linus Holtermann
• [R-sig-ME] nlme : how to obtain confidence intervals of fitted values   Laura Riggi
• [R-sig-ME] nlme : how to obtain confidence intervals of fitted values   Ben Bolker
• [R-sig-ME] nlme package: changing reference for varIdent parameter estimates in summary.gls   Kornak, John
• [R-sig-ME] nlme predict   Vasco Cadavez
• [R-sig-ME] nlme predict   romunov
• [R-sig-ME] Non-diagonal sampling covariance with lme4   Asaf Weinstein
• [R-sig-ME] Non-diagonal sampling covariance with lme4   Douglas Bates
• [R-sig-ME] Non-diagonal sampling covariance with lme4   Ben Bolker
• [R-sig-ME] Non-diagonal sampling covariance with lme4   Asaf Weinstein
• [R-sig-ME] Offset() in gls() in nlme   Mark Payne
• [R-sig-ME] Offset() in gls() in nlme   ONKELINX, Thierry
• [R-sig-ME] Offset() in gls() in nlme   Douglas Bates
• [R-sig-ME] Offset() in gls() in nlme   Mark Payne
• [R-sig-ME] Offset() in gls() in nlme   Ben Bolker
• [R-sig-ME] Openblas and lme4   Christian Brauner
• [R-sig-ME] Openblas and lme4   Douglas Bates
• [R-sig-ME] Ordinal categorical variable as a random effect in MCMCglmm   Manabu Sakamoto
• [R-sig-ME] Ordinal categorical variable as a random effect in MCMCglmm   Jarrod Hadfield
• [R-sig-ME] Ordinal categorical variable as a random effect in MCMCglmm   Manabu Sakamoto
• [R-sig-ME] Ordinal categorical variable as a random effect in MCMCglmm   Jarrod Hadfield
• [R-sig-ME] parallel option of the bootMer function: warnings for parallel=no, but not for parallel=snow   Spronken, M. (Maitta)
• [R-sig-ME] parallel option of the bootMer function: warnings for parallel=no, but not for parallel=snow   Ben Bolker
• [R-sig-ME] parallel option of the bootMer function: warnings for parallel=no, but not for parallel=snow   Spronken, M. (Maitta)
• [R-sig-ME] parallel option of the bootMer function: warnings for parallel=no, but not for parallel=snow   Spronken, M. (Maitta)
• [R-sig-ME] parallel option of the bootMer function: warnings for parallel=no, but not for parallel=snow   Henrik Singmann
• [R-sig-ME] parallel option of the bootMer function: warnings for parallel=no, but not for parallel=snow   Spronken, M. (Maitta)
• [R-sig-ME] Partial R2 in mixed models   Joan Molibo
• [R-sig-ME] Partial R2 in mixed models   Joan Molibo
• [R-sig-ME] Partial R2 in mixed models   Joan Molibo
• [R-sig-ME] Post model fitting checks in Metafor (rma.mv)   Shona Smith
• [R-sig-ME] predict.MCMCglmm() does not use random effects?   Jonas Lindeløv
• [R-sig-ME] predict.MCMCglmm() does not use random effects?   Jarrod Hadfield
• [R-sig-ME] predict GAMM   Rafael Wüest
• [R-sig-ME] Problem with bootMer and models with offset   Martin Hecht
• [R-sig-ME] Problem with bootMer and models with offset   Ben Bolker
• [R-sig-ME] Problem with bootMer and models with offset   Martin Hecht
• [R-sig-ME] Problem with bootMer and models with offset   Martin Hecht
• [R-sig-ME] Problem with bootMer and models with offset   Ben Bolker
• [R-sig-ME] Problem with bootMer and models with offset   Martin Hecht
• [R-sig-ME] Proportional Error model in nlme using weights   Farkad Ezzet
• [R-sig-ME] Proportional Error model in nlme using weights   Farkad Ezzet
• [R-sig-ME] question regarding multiple subjects in lmer   Francisco Juretig
• [R-sig-ME] R-sig-mixed-models Digest, Vol 94, Issue 38   Szymek Drobniak
• [R-sig-ME] R-sig-mixed-models Digest, Vol 95, Issue 21   Mayara Amescua
• [R-sig-ME] R-sig-mixed-models Digest, Vol 95, Issue 6   Luciano La Sala
• [R-sig-ME] R-sig-mixed-models Digest, Vol 95, Issue 6   Ken Beath
• [R-sig-ME] R-sig-mixed-models Digest, Vol 95, Issue 6   Ben Bolker
• [R-sig-ME] R-sig-mixed-models Digest, Vol 95, Issue 8   Luciano La Sala
• [R-sig-ME] R2 for Negative Binomial calculated with GLMMADMB   Jens Oldeland
• [R-sig-ME] R2 for Negative Binomial calculated with GLMMADMB   Douglas Bates
• [R-sig-ME] R2 for Negative Binomial calculated with GLMMADMB   Kevin Wright
• [R-sig-ME] R2 for Negative Binomial calculated with GLMMADMB   Rolf Turner
• [R-sig-ME] R2 for Negative Binomial calculated with GLMMADMB   Jens Oldeland
• [R-sig-ME] R2 for Negative Binomial calculated with GLMMADMB   Ben Bolker
• [R-sig-ME] R2 for Negative Binomial calculated with GLMMADMB   Shinichi Nakagawa
• [R-sig-ME] R2 for Negative Binomial calculated with GLMMADMB   Simon Blomberg
• [R-sig-ME] R2 for Negative Binomial calculated with GLMMADMB   Ben Bolker
• [R-sig-ME] R2 for Negative Binomial calculated with GLMMADMB   Jens Oldeland
• [R-sig-ME] Repeated Measures in MCMCglmm model   Tricia Markle
• [R-sig-ME] Repeated Measures in MCMCglmm model   Jarrod Hadfield
• [R-sig-ME] Repeated Measures in MCMCglmm model   Tricia Markle
• [R-sig-ME] response correlated among groups   Rafael Wüest
• [R-sig-ME] response correlated among groups   Ben Bolker
• [R-sig-ME] Robust SEs in GLMMs   Sharon Poessel
• [R-sig-ME] Robust SEs in GLMMs   Tim Meehan
• [R-sig-ME] Robust SEs in GLMMs   Sharon Poessel
• [R-sig-ME] Robust SEs in GLMMs   Tim Meehan
• [R-sig-ME] Robust SEs in GLMMs   Douglas Bates
• [R-sig-ME] Robust SEs in GLMMs   Tim Meehan
• [R-sig-ME] Robust SEs in GLMMs   Douglas Bates
• [R-sig-ME] Robust SEs in GLMMs   Ben Bolker
• [R-sig-ME] Robust SEs in GLMMs   Tim Meehan
• [R-sig-ME] Robust SEs in GLMMs   Ken Beath
• [R-sig-ME] Robust SEs in GLMMs   Sharon Poessel
• [R-sig-ME] Robust SEs in GLMMs   David Duffy
• [R-sig-ME] Robust SEs in GLMMs   Chris Howden
• [R-sig-ME] Setting parameters to 0   Wafic El - Assi
• [R-sig-ME] Setting parameters to 0   ONKELINX, Thierry
• [R-sig-ME] singular convergence warning   Price, Emily
• [R-sig-ME] singular convergence warning   romunov
• [R-sig-ME] standard error and statistical significance in lmer versus lm   Vincenzo Lagani
• [R-sig-ME] standard error and statistical significance in lmer versus lm   Ben Bolker
• [R-sig-ME] subject level predictions with lme4 from incomplete longitudinal profile   Tarca, Adi
• [R-sig-ME] subject level predictions with lme4 from incomplete longitudinal profile   Ben Bolker
• [R-sig-ME] subject level predictions with lme4 from incomplete longitudinal profile   Tarca, Adi
• [R-sig-ME] Survey weights. Suggestions?   Paul Johnson
• [R-sig-ME] Survey weights. Suggestions?   W Robert Long
• [R-sig-ME] testing for a significant correlation between random slopes   Bill Shipley
• [R-sig-ME] testing for a significant correlation between random slopes   Jaime Ashander
• [R-sig-ME] testing for a significant correlation between random slopes   Ben Bolker
• [R-sig-ME] testing for a significant correlation between random slopes (Jaime Ashander)   Tove Jansson
• [R-sig-ME] Testing interaction between fixed effect and random effect nested within another random effect   Eoin Duffy
• [R-sig-ME] Testing interaction between fixed effect and random effect nested within another random effect   ONKELINX, Thierry
• [R-sig-ME] trait specific fixed effects for bivariate model in MCMCglmm   Kristina Noreikiene
• [R-sig-ME] trait specific fixed effects for bivariate model in MCMCglmm   Kristina Noreikiene
• [R-sig-ME] trait specific fixed effects for bivariate model in MCMCglmm   Jarrod Hadfield
• [R-sig-ME] varFixed function query in lme   Douglas Bates
• [R-sig-ME] varFixed function query in lme   Ben Bolker
• [R-sig-ME] very different model estimates in GLM vs. GLMM   Vincenzo Ellis
• [R-sig-ME] very different model estimates in GLM vs. GLMM   ONKELINX, Thierry
• [R-sig-ME] very different model estimates in GLM vs. GLMM   Vincenzo Ellis
• [R-sig-ME] very different model estimates in GLM vs. GLMM   ONKELINX, Thierry
• [R-sig-ME] weights = varIdent - differences even if "weighted factor" is not in the model   Friso Muijsers
• [R-sig-ME] When to use random slop models   Mohd Masood
• [R-sig-ME] Zero-inflated and proportional data   Mayara Amescua
• [R-sig-ME] Zero-inflated and proportional data   Marc Schwartz
• [R-sig-ME] Zero-inflated and proportional data   Highland Statistics Ltd

Last message date: Mon Dec 29 06:53:53 CET 2014
Archived on: Mon Dec 29 06:54:05 CET 2014

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