Second quarter 2017 Archives by thread

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Starting: Sat Apr 1 10:19:33 CEST 2017
Ending: Thu Jun 22 21:15:53 CEST 2017
Messages: 227

• [R-sig-ME] Modelling proportion data in lme4   Ramon Diaz-Uriarte
  • [R-sig-ME] Modelling proportion data in lme4   Adriana De Palma
    • [R-sig-ME] Modelling proportion data in lme4   guillaume chaumet
      • [R-sig-ME] Modelling proportion data in lme4   Ramon Diaz-Uriarte
• [R-sig-ME] Using lme function in R in a brain imaging study   Ilgim Hepdarcan
  • [R-sig-ME] Using lme function in R in a brain imaging study   Phillip Alday
• [R-sig-ME] marginal R square calculation in zero truncated poisson model   Paul Johnson
• [R-sig-ME] A question on setting up a generalized additive mixed effect model   Leon Lee
• [R-sig-ME] [External] Re: nlme & varIdent   Louisell, Paul T PW
  • [R-sig-ME] lmer-model - model ok? (control condition, random effects, log transformation)   Diana Michl
    • [R-sig-ME] lmer-model - model ok? (control condition, random effects, log transformation)   Diana Michl
    • [R-sig-ME] lmer-model - model ok? (control condition, random effects, log transformation)   Phillip Alday
• [R-sig-ME] Fwd: GLM-normal distribution   Marcos Monasterolo
  • [R-sig-ME] Fwd: GLM-normal distribution   Ben Bolker
  • [R-sig-ME] Fwd: GLM-normal distribution   Steven J. Pierce
• [R-sig-ME] prior specification for multinomial model MCMCglmm   Vincenzo Ellis
  • [R-sig-ME] prior specification for multinomial model MCMCglmm   HAJDUK Gabriela
  • [R-sig-ME] prior specification for multinomial model MCMCglmm   Jarrod Hadfield
• [R-sig-ME] mgcv gam/bam model selection with random effects and AR terms   Mathew Guilfoyle
• [R-sig-ME] Specifying models nested crossed random effects   Joshua Rosenberg
  • [R-sig-ME] Specifying models nested crossed random effects   Evan Palmer-Young
    • [R-sig-ME] Specifying models nested crossed random effects   Joshua Rosenberg
      • [R-sig-ME] Specifying models nested crossed random effects   Evan Palmer-Young
      • [R-sig-ME] Specifying models nested crossed random effects   Joshua Rosenberg
      • [R-sig-ME] Specifying models nested crossed random effects   Joshua Rosenberg
      • [R-sig-ME] Specifying models nested crossed random effects   Ben Bolker
      • [R-sig-ME] Specifying models nested crossed random effects   Joshua Rosenberg
      • [R-sig-ME] Specifying models nested crossed random effects   Diana Michl
      • [R-sig-ME] Specifying models nested crossed random effects   Phillip Alday
• [R-sig-ME] Mixed effects for Discrete Time or Grouped Time Survival Analysis   Phillip Alday
• [R-sig-ME] LMER: Visualizing three-way interaction   Klemens Knöferle
  • [R-sig-ME] LMER: Visualizing three-way interaction   Evan Palmer-Young
    • [R-sig-ME] LMER: Visualizing three-way interaction   Thierry Onkelinx
      • [R-sig-ME] LMER: Visualizing three-way interaction   Ulf Köther
  • [R-sig-ME] LMER: Visualizing three-way interaction   Ramon Diaz-Uriarte
• [R-sig-ME] Visualizing three-way interaction   Houslay, Tom
  • [R-sig-ME] Visualizing three-way interaction   Klemens Knöferle
• [R-sig-ME] mixture DIC model   Mohammadreza Kordbagheri
  • [R-sig-ME] mixture DIC model   Ben Bolker
• [R-sig-ME] Fwd: Continuous variable as random slope and the minimum number of levels for a categorical variable to be treated as random   Michele Scandola
  • [R-sig-ME] Fwd: Continuous variable as random slope and the minimum number of levels for a categorical variable to be treated as random   Conor Michael Goold
    • [R-sig-ME] Fwd: Continuous variable as random slope and the minimum number of levels for a categorical variable to be treated as random   Michele Scandola
      • [R-sig-ME] Fwd: Continuous variable as random slope and the minimum number of levels for a categorical variable to be treated as random   Conor Michael Goold
  • [R-sig-ME] Fwd: Continuous variable as random slope and the minimum number of levels for a categorical variable to be treated as random   Szymek Drobniak
• [R-sig-ME] New version of afex on CRAN now   Henrik Singmann
• [R-sig-ME] Modelling count data in glmer with an apriori model selection   Lorraine Scotson
  • [R-sig-ME] Modelling count data in glmer with an apriori model selection   Ben Bolker
• [R-sig-ME] Modeling attacks and victories   Paul Johnson
  • [R-sig-ME] Modeling attacks and victories   Peter Claussen
  • [R-sig-ME] Modeling attacks and victories   Poe, John
  • [R-sig-ME] Modeling attacks and victories   Thierry Onkelinx
    • [R-sig-ME] Modeling attacks and victories   Paul Johnson
• [R-sig-ME] nested effects for only a small subset of situations   Robert Chatfield
• [R-sig-ME] Fwd: glmmTMB, glmmADMB for a proportion RV with 0- (and 1-?) inflation   simone santoro
• [R-sig-ME] GLMM for Combined experiments and overdispersed data   Juan Pablo Edwards Molina
  • [R-sig-ME] GLMM for Combined experiments and overdispersed data   Thierry Onkelinx
    • [R-sig-ME] GLMM for Combined experiments and overdispersed data   Juan Pablo Edwards Molina
      • [R-sig-ME] GLMM for Combined experiments and overdispersed data   Peter Claussen
      • [R-sig-ME] GLMM for Combined experiments and overdispersed data   Thierry Onkelinx
      • [R-sig-ME] GLMM for Combined experiments and overdispersed data   Juan Pablo Edwards Molina
      • [R-sig-ME] GLMM for Combined experiments and overdispersed data   Juan Pablo Edwards Molina
      • [R-sig-ME] GLMM for Combined experiments and overdispersed data   Thierry Onkelinx
      • [R-sig-ME] GLMM for Combined experiments and overdispersed data   Peter Claussen
      • [R-sig-ME] GLMM for Combined experiments and overdispersed data   Peter Claussen
• [R-sig-ME] Plot model average   Pin chanratana
• [R-sig-ME] Hi listers   Said Ali Shah
  • [R-sig-ME] Hi listers   Andrew Robinson
  • [R-sig-ME] Hi listers   Malcolm Fairbrother
• [R-sig-ME] question about nlmer   voigt.charlotte at web.de
• [R-sig-ME] mixed model?   Joaquín Aldabe
  • [R-sig-ME] mixed model?   Evan Palmer-Young
    • [R-sig-ME] mixed model?   Joaquín Aldabe
      • [R-sig-ME] mixed model?   Ben Bolker
      • [R-sig-ME] mixed model?   Joaquín Aldabe
      • [R-sig-ME] mixed model?   Evan Palmer-Young
      • [R-sig-ME] mixed model?   Evan Palmer-Young
      • [R-sig-ME] mixed model?   Ben Bolker
      • [R-sig-ME] mixed model?   Joaquín Aldabe
• [R-sig-ME] zero-inflation and multimodal count distribution   simone santoro
  • [R-sig-ME] zero-inflation and multimodal count distribution   Ben Bolker
    • [R-sig-ME] zero-inflation and multimodal count distribution   Ben Bolker
• [R-sig-ME] persistant autocorrelation in binomial MCMCglmm   Aiello, Christina
  • [R-sig-ME] persistant autocorrelation in binomial MCMCglmm   Jarrod Hadfield
    • [R-sig-ME] persistant autocorrelation in binomial MCMCglmm   Aiello, Christina
      • [R-sig-ME] persistant autocorrelation in binomial MCMCglmm   Aiello, Christina
• [R-sig-ME] mixed model for nested factor?   Jinsong Zhao
  • [R-sig-ME] mixed model for nested factor?   Thierry Onkelinx
    • [R-sig-ME] mixed model for nested factor?   Jinsong Zhao
      • [R-sig-ME] mixed model for nested factor?   Thierry Onkelinx
• [R-sig-ME] Animal model residual value   Walid
  • [R-sig-ME] Animal model residual value   Pierre de Villemereuil
  • [R-sig-ME] Animal model residual value   timothee.bonnet at ieu.uzh.ch
    • [R-sig-ME] Animal model residual value   Walid
• [R-sig-ME] Fwd: Re: R-core post from jw1085 at wildcats.unh.edu requires approval   Jochen Wirsing
  • [R-sig-ME] Fwd: Re: R-core post from jw1085 at wildcats.unh.edu requires approval   Mitchell Maltenfort
  • [R-sig-ME] Fwd: Re: R-core post from jw1085 at wildcats.unh.edu requires approval   Thierry Onkelinx
  • [R-sig-ME] Fwd: Re: R-core post from jw1085 at wildcats.unh.edu requires approval   Kevin Wright
    • [R-sig-ME] Fwd: Re: R-core post from jw1085 at wildcats.unh.edu requires approval   Ben Bolker
      • [R-sig-ME] Fwd: Re: R-core post from jw1085 at wildcats.unh.edu requires approval   Ben Bolker
• [R-sig-ME] A question on using LME model in species nested within a random block design   Faming Wang
  • [R-sig-ME] A question on using LME model in species nested within a random block design   Phillip Alday
    • [R-sig-ME] 答复: A question on using LME model in species nested within a random block design   famingw at gmail.com
  • [R-sig-ME] A question on using LME model in species nested within a random block design   Faming Wang
    • [R-sig-ME] A question on using LME model in species nested within a random block design   Seth Bigelow
      • [R-sig-ME] A question on using LME model in species nested within a random block design   Faming Wang
• [R-sig-ME] nlme issue   Jochen Wirsing
  • [R-sig-ME] nlme issue   Jeff Newmiller
• [R-sig-ME] nlme issue since 3.40   Jochen Wirsing
  • [R-sig-ME] nlme issue since 3.40   Philippi, Tom
    • [R-sig-ME] nlme issue since 3.40   Torsten Hauffe
      • [R-sig-ME] nlme issue since 3.40   Jochen Wirsing
    • [R-sig-ME] nlme issue since 3.40   Jinsong Zhao
• [R-sig-ME] Dealing with very high autocorrelations in logistic MCMCglmm   Raffaele Vacca
  • [R-sig-ME] Split plot repeated measurements + slope comparison   Nicolas Fanin
• [R-sig-ME] Multilevel logistic regression guessing parameter   Dominik Ćepulić
  • [R-sig-ME] Multilevel logistic regression guessing parameter   Phillip Alday
    • [R-sig-ME] Multilevel logistic regression guessing parameter   Jake Westfall
  • [R-sig-ME] Multilevel logistic regression guessing parameter   Paul Buerkner
    • [R-sig-ME] Multilevel logistic regression guessing parameter   Dominik Ćepulić
      • [R-sig-ME] Multilevel logistic regression guessing parameter   Doran, Harold
      • [R-sig-ME] Multilevel logistic regression guessing parameter   Dominik Ćepulić
      • [R-sig-ME] Multilevel logistic regression guessing parameter   Doran, Harold
    • [R-sig-ME] Multilevel logistic regression guessing parameter   Paul Buerkner
      • [R-sig-ME] Multilevel logistic regression guessing parameter   Conor Michael Goold
      • [R-sig-ME] Multilevel logistic regression guessing parameter   Jonathan Baron
      • [R-sig-ME] Multilevel logistic regression guessing parameter   Conor Michael Goold
      • [R-sig-ME] Multilevel logistic regression guessing parameter   Dominik Ćepulić
      • [R-sig-ME] Multilevel logistic regression guessing parameter   Conor Michael Goold
      • [R-sig-ME] Multilevel logistic regression guessing parameter   Dominik Ćepulić
      • [R-sig-ME] Multilevel logistic regression guessing parameter   Jonathan Baron
      • [R-sig-ME] Multilevel logistic regression guessing parameter   Conor Michael Goold
  • [R-sig-ME] Multilevel logistic regression guessing parameter   Kenneth Knoblauch
• [R-sig-ME] Predicting individual slopes from specific random intercepts   Dominik Ćepulić
• [R-sig-ME] ERPs lme covariates   Alexandre Obert
• [R-sig-ME] Syntax interaction polynomial term   Luca Corlatti
  • [R-sig-ME] Syntax interaction polynomial term   Thierry Onkelinx
• [R-sig-ME] A mixed effect regression tool based on bayesian priors like bayesglm   Angelo D'Ambrosio
• [R-sig-ME] Mixed models for repeated measures with missing values   Hongmei Chen
• [R-sig-ME] Warnings BootMer bootstrap glmer lme4   D.J. Damen
  • [R-sig-ME] Warnings BootMer bootstrap glmer lme4   Ben Bolker
  • [R-sig-ME] Warnings BootMer bootstrap glmer lme4   D.J. Damen
• [R-sig-ME] Help with glmmADMB and ZIP mixed effects models   Wang, Shirley
  • [R-sig-ME] Help with glmmADMB and ZIP mixed effects models   simone santoro
  • [R-sig-ME] Help with glmmADMB and ZIP mixed effects models   Ben Bolker
• [R-sig-ME] Suggestion for Model convergence problem:non-positive-definite Hessian matrix.   Ben Bolker
• [R-sig-ME] wider than expected confidence intervals with lsmeans and predict.glmmadmb   Evan Palmer-Young
  • [R-sig-ME] wider than expected confidence intervals with lsmeans and predict.glmmadmb   John Maindonald
    • [R-sig-ME] wider than expected confidence intervals with lsmeans and predict.glmmadmb   Evan Palmer-Young
      • [R-sig-ME] wider than expected confidence intervals with lsmeans and predict.glmmadmb   John Maindonald
  • [R-sig-ME] wider than expected confidence intervals with lsmeans and predict.glmmadmb   Lenth, Russell V
    • [R-sig-ME] wider than expected confidence intervals with lsmeans and predict.glmmadmb   Evan Palmer-Young
      • [R-sig-ME] wider than expected confidence intervals with lsmeans and predict.glmmadmb   Ben Bolker
      • [R-sig-ME] wider than expected confidence intervals with lsmeans and predict.glmmadmb   Evan Palmer-Young
• [R-sig-ME] statistical significance of group level intercepts in glmer   Maaz Gardezi
  • [R-sig-ME] statistical significance of group level intercepts in glmer   Ben Bolker
    • [R-sig-ME] statistical significance of group level intercepts in glmer   Maaz Gardezi
      • [R-sig-ME] glmmPQL: std.errors in summary and vcov differ   Ben Pelzer
      • [R-sig-ME] glmmPQL: std.errors in summary and vcov differ   Ben Bolker
      • [R-sig-ME] glmmPQL: std.errors in summary and vcov differ   Steve Candy
• [R-sig-ME] Partitioning species and environment effects MCMCglmm   Demétrius Martins
  • [R-sig-ME] Fwd: Partitioning species and environment effects MCMCglmm   Demétrius Martins
• [R-sig-ME] lme4 convergence warnings & model notation   Ender Raphael
• [R-sig-ME] Deviations from normality in MCMC models   Christopher Robinson
  • [R-sig-ME] Deviations from normality in MCMC models   landon hurley
    • [R-sig-ME] Deviations from normality in MCMC models   Ben Bolker
      • [R-sig-ME] Deviations from normality in MCMC models   Evan Palmer-Young
• [R-sig-ME] Formula df when combining imputed data   Ben Pelzer
  • [R-sig-ME] Formula df when combining imputed data   Ben Pelzer
• [R-sig-ME] afex in missing data (when testing main effects in presence of interactions in factorial designs)   Thomas Deimel
  • [R-sig-ME] afex in missing data (when testing main effects in presence of interactions in factorial designs)   Henrik Singmann
    • [R-sig-ME] afex in missing data (when testing main effects in presence of interactions in factorial designs)   Alday, Phillip
      • [R-sig-ME] afex in missing data (when testing main effects in presence of interactions in factorial designs)   Thomas Deimel
    • [R-sig-ME] afex in missing data (when testing main effects in presence of interactions in factorial designs)   Alday, Phillip
• [R-sig-ME] Predict and plot lines estimated from MCMCglmm?   Jesse Delia
  • [R-sig-ME] Predict and plot lines estimated from MCMCglmm?   Malcolm Fairbrother
• [R-sig-ME] gamm plots in lattice   Maria Lathouri
  • [R-sig-ME] gamm plots in lattice   Ulf Köther
    • [R-sig-ME] gamm plots in lattice   Ulf Köther
• [R-sig-ME] Bglmer convergence warnings (covariance structure)   D.J. Damen
  • [R-sig-ME] Bglmer convergence warnings (covariance structure)   Ben Bolker
• [R-sig-ME] Interpreting variances for random effects   Chen, Gang (NIH/NIMH) [C]
• [R-sig-ME] [R] understanding I() in lmer formula   Don Cohen
  • [R-sig-ME] [R] understanding I() in lmer formula   peter dalgaard
  • [R-sig-ME] [R] understanding I() in lmer formula   Andrew Robinson
    • [R-sig-ME] [R] understanding I() in lmer formula   Dan Brooks
      • [R-sig-ME] [R] understanding I() in lmer formula   Ben Bolker
    • [R-sig-ME] [R] understanding I() in lmer formula   Don Cohen
      • [R-sig-ME] [R] understanding I() in lmer formula   Emmanuel Curis
      • [R-sig-ME] [R] understanding I() in lmer formula   Emmanuel Curis
      • [R-sig-ME] [R] understanding I() in lmer formula   Don Cohen
      • [R-sig-ME] [R] understanding I() in lmer formula   Don Cohen
      • [R-sig-ME] [R] understanding I() in lmer formula   Emmanuel Curis
      • [R-sig-ME] [R] understanding I() in lmer formula   Ben Bolker
      • [R-sig-ME] [R] understanding I() in lmer formula   Don Cohen
      • [R-sig-ME] [R] understanding I() in lmer formula   Don Cohen
      • [R-sig-ME] [R] understanding I() in lmer formula   Ben Bolker
      • [R-sig-ME] [R] understanding I() in lmer formula   Don Cohen
      • [R-sig-ME] [R] understanding I() in lmer formula   Ben Bolker
      • [R-sig-ME] [R] understanding I() in lmer formula   Don Cohen
  • [R-sig-ME] [R] understanding I() in lmer formula   Don Cohen
    • [R-sig-ME] [R] understanding I() in lmer formula   Marc Schwartz
      • [R-sig-ME] [R] understanding I() in lmer formula   Ben Bolker
      • [R-sig-ME] [R] understanding I() in lmer formula   Ben Bolker
      • [R-sig-ME] [R] understanding I() in lmer formula   Don Cohen
      • [R-sig-ME] [R] understanding I() in lmer formula   David Winsemius
      • [R-sig-ME] [R] understanding I() in lmer formula   Don Cohen
      • [R-sig-ME] [R] understanding I() in lmer formula   Ben Bolker
      • [R-sig-ME] [R] understanding I() in lmer formula   Don Cohen
      • [R-sig-ME] [R] understanding I() in lmer formula   David Winsemius
      • [R-sig-ME] [R] understanding I() in lmer formula   Ben Bolker
• [R-sig-ME] Problems loading lme4 module into R   rudolf.marty2 at ccrs.uzh.ch
  • [R-sig-ME] Problems loading lme4 module into R   Mollie Brooks
    • [R-sig-ME] Problems loading lme4 module into R   Jeff Newmiller
• [R-sig-ME] Question glmmADMB   Wouter Broos
  • [R-sig-ME] Question glmmADMB   Rolf Turner
  • [R-sig-ME] Question glmmADMB   Mollie Brooks
    • [R-sig-ME] Question glmmADMB   Ben Bolker
• [R-sig-ME] simulating a linear random intercept model with exogeneity assumption   mervat mohamed
  • [R-sig-ME] Fw: simulating a linear random intercept model with exogeneity assumption   mervat mohamed
• [R-sig-ME] Power calculations for lmer mixed designs   Diana Michl
• [R-sig-ME] Fwd: Re: Power calculations for lmer mixed designs   Phillip Alday
  • [R-sig-ME] Fwd: Re: Power calculations for lmer mixed designs   Diana Michl
• [R-sig-ME] New book: Spatial, Temporal and Spatial-Temporal Ecological Data Analysis with R-INLA   Highland Statistics Ltd
• [R-sig-ME] response variable distribution-MCMCglmm   Walid
  • [R-sig-ME] response variable distribution-MCMCglmm   Paul Buerkner
    • [R-sig-ME] response variable distribution-MCMCglmm   Mollie Brooks
• [R-sig-ME] Distinction between nAGQ=0 and nAGQ=1 in glmer   Douglas Bates

Last message date: Thu Jun 22 21:15:53 CEST 2017
Archived on: Thu Jun 22 21:16:10 CEST 2017

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