To check whether the data are being read in appropriately, what happens when you plot the distribution of each of the independent variables on the respective systems?
-A On Wed, 5 Jun 2019 12:32:28 +0200 Olivier Crouzet <olivier.crou...@univ-nantes.fr> wrote: > Hi, > > 32bit vs. 64bit systems? > > Another thing I would look at would be how the windows machine will > read the data file. Though issues should probably only arise with > respect to text data, I've often experienced problems with reading > unicode csv files on windows computers compared with unix-based > computers. No guarantee though, just suggestions... > > Olivier. > > On Wed, 5 Jun 2019 12:15:53 +0200 > Nicolas Schuck <nico.sch...@gmail.com> wrote: > > > bert: you are right, sorry for not cc-ing the list. thanks also for > > the hint. > > > > I wanted to bring this up here again, emphasising that we do find in > > at least one case *a very large difference* in the p value, using > > the same scripts and data on a windows versus mac machine (see > > reproducible example in the gitlab link posted below). I have now > > come across several instances in which results of (g)lmer models > > don’t agree on windows vs unix-based machines, which I find a bit > > disturbing. any ideas where non-negligible differences could come > > from? > > > > thanks, > > nico > > > > > > > On 30. May 2019, at 16:58, Bert Gunter <bgunter.4...@gmail.com> > > > wrote: > > > > > > > > > Unless there us good reason not to, always cc the list. I have > > > done so here. > > > > > > The R Installation manual has some info on how to use different > > > BLASes I believe, but someone with expertise (I have none) needs > > > to respond to your queries. > > > > > > On Thu, May 30, 2019 at 7:50 AM Nicolas Schuck > > > <nico.sch...@gmail.com <mailto:nico.sch...@gmail.com>> wrote: I > > > know that it is in use on the Mac, see sessionInfo below. I have > > > to check on the Win system. Why would that make such a difference > > > and how could I make the Win get the same results as the Unix > > > Systems? > > > > > > R version 3.6.0 (2019-04-26) > > > Platform: x86_64-apple-darwin15.6.0 (64-bit) > > > Running under: macOS Mojave 10.14.5 > > > Matrix products: default > > > BLAS: > > > /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib > > > > > > LAPACK: > > > /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib > > > > > > Random number generation: > > > RNG: Mersenne-Twister > > > Normal: Inversion Sample: Rounding > > > locale: [1] > > > en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 > > > attached base packages: [1] stats graphics grDevices utils > > > datasets methods base Thanks, Nico On 30. May 2019, at 16:34, > > > Bert Gunter <bgunter.4...@gmail.com > > > <mailto:bgunter.4...@gmail.com>> wrote: > > > > > >> The BLAS in use on each? > > >> > > >> Bert Gunter > > >> > > >> "The trouble with having an open mind is that people keep coming > > >> along and sticking things into it." > > >> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip > > >> ) > > >> > > >> > > >> On Thu, May 30, 2019 at 5:27 AM Nicolas Schuck > > >> <nico.sch...@gmail.com <mailto:nico.sch...@gmail.com>> wrote: > > >> Dear fellow R coders, > > >> > > >> I am observing differences in results obtained using glmer when > > >> using a Mac or Linux computer versus a PC. Specifically, I am > > >> talking about a relatively complex glmer model with a nested > > >> random effects structure. The model is set up in the following > > >> way: gcctrl = glmerControl(optimizer=c('nloptwrap'), optCtrl = > > >> list (maxfun = 500000), calc.derivs = FALSE) > > >> > > >> glmer_pre_instr1 = glmer( > > >> formula = cbind(FREQ, NSAMP-FREQ) ~ FDIST_minz + poly > > >> (RFREQ,2) + ROI + (1 + FDIST_minz + RFREQ + ROI|ID/COL), data = > > >> cdf_pre_instr, family = binomial, > > >> control = gcctrl) > > >> > > >> Code and data of an example for which I find reproducible, > > >> non-negligible differences between Mac/Win can be found here: > > >> https://gitlab.com/nschuck/glmer_sandbox/tree/master > > >> <https://gitlab.com/nschuck/glmer_sandbox/tree/master> > > >> <https://gitlab.com/nschuck/glmer_sandbox/tree/master > > >> <https://gitlab.com/nschuck/glmer_sandbox/tree/master>> The > > >> differences between the fitted models seem to be most pronounced > > >> regarding the estimated correlation structure of the random > > >> effects terms. Mac and Linux yield very similar results, but > > >> Windows deviates quite a bit in some cases. This has a large > > >> impact on p values obtained when performing model comparisons. I > > >> have tried this on Mac OS 10.14, Windows 10 and Ubuntu and > > >> Debian. All systems I have tried are using lme 1.1.21 and R > > >> 3.5+. > > >> > > >> Does anyone have an idea what the underlying cause might be? > > >> > > >> Thanks, > > >> Nico > > >> > > >> > > >> > > >> > > >> [[alternative HTML version deleted]] > > >> > > >> ______________________________________________ > > >> R-help@r-project.org <mailto:R-help@r-project.org> mailing list > > >> -- To UNSUBSCRIBE and more, see > > >> https://stat.ethz.ch/mailman/listinfo/r-help > > >> <https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the > > >> posting guide http://www.R-project.org/posting-guide.html > > >> <http://www.r-project.org/posting-guide.html> and provide > > >> commented, minimal, self-contained, reproducible code. > > > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > > http://www.R-project.org/posting-guide.html and provide commented, > > minimal, self-contained, reproducible code. > > ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
