No, apologies (good catch David!), I merely copied the script incorrectly. It was
lmer(Y~X + (1|labs),data=DATA) in my original script. So my question still stands: is it expected behavior for lmer to access the object 'labs' rather than the object 'DATA$labs' when using the data= argument? JJ On Wed, Aug 18, 2010 at 11:29 AM, David Winsemius <dwinsem...@comcast.net>wrote: > > On Aug 18, 2010, at 1:19 PM, Johan Jackson wrote: > > Hi all, >> >> Thanks for the replies (including off list). I have since resolved the >> discrepant results. I believe it has to do with R's scoping rules - I had >> an >> object called 'labs' and a variable in the dataset (DATA) called 'labs', >> and >> apparently (to my surprise), when I called this: >> >> lmer(Y~X + (1|labs),dataset=DATA) >> >> lmer was using the object 'labs' rather than the object 'DATA$labs'. Is >> this >> expected behavior?? >> > > help(lmer, package=lme4) > > It would be if you use the wrong data argument for lmer(). I doubt that the > argument "dataset" would result in lmer processing "DATA". My guess is that > the function also accessed objects "Y" and "X" from the calling environment > rather than from within "DATA". > > > > >> This would have been fine, except I had reordered DATA in the meantime! >> >> Best, >> >> JJ >> >> On Tue, Aug 17, 2010 at 7:17 PM, Mitchell Maltenfort <mmal...@gmail.com >> >wrote: >> >> One difference is that the random effect in lmer is assumed -- >>> implicitly constrained, as I understand it -- to >>> be a bell curve. The fixed effect model does not have that constraint. >>> >>> How are the values of "labs" effects distributed in your lm model? >>> >>> On Tue, Aug 17, 2010 at 8:50 PM, Johan Jackson >>> <johan.h.jack...@gmail.com> wrote: >>> >>>> Hello, >>>> >>>> Setup: I have data with ~10K observations. Observations come from 16 >>>> different laboratories (labs). I am interested in how a continuous >>>> >>> factor, >>> >>>> X, affects my dependent variable, Y, but there are big differences in >>>> the >>>> variance and mean across labs. >>>> >>>> I run this model, which controls for mean but not variance differences >>>> between the labs: >>>> lm(Y ~ X + as.factor(labs)). >>>> The effect of X is highly significant (p < .00001) >>>> >>>> I then run this model using lme4: >>>> lmer(Y~ X + (1|labs)) #controls for mean diffs bw labs >>>> lmer(Y~X + (X|labs)) #and possible slope heterogeneity bw labs. >>>> >>>> For both of these latter models, the effect of X is non-significant (|t| >>>> >>> < >>> >>>> 1.5). >>>> >>>> What might this be telling me about my data? I guess the second (X|labs) >>>> >>> may >>> >>>> tell me that there are big differences in the slope across labs, and >>>> that >>>> the slope isn't significant against the backdrop of 16 slopes that >>>> differ >>>> quite a bit between each other. Is that right? (Still, the enormous drop >>>> >>> in >>> >>>> p-value is surprising!). I'm not clear on why the first (1|labs), >>>> >>> however, >>> >>>> is so discrepant from just controlling for the mean effects of labs. >>>> >>>> Any help in interpreting these data would be appreciated. When I first >>>> >>> saw >>> >>>> the data, I jumped for joy, but now I'm muddled and uncertain if I'm >>>> overlooking something. Is there still room for optimism (with respect to >>>> >>> X >>> >>>> affecting Y)? >>>> >>>> JJ >>>> >>>> [[alternative HTML version deleted]] >>>> >>>> ______________________________________________ >>>> R-help@r-project.org mailing list >>>> 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. >>>> >>>> >>> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list >> 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. >> > > David Winsemius, MD > West Hartford, CT > > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list 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.
