Thank you for pointing ou R-forge. I tried link from R-forge for lme4a, it doesn't work at the time I tried (Returned "PAGE NOT FOUND". However, the link for lme4b worked, and I installed lme4b package which can be loaded successfully. lme4b has lmer1() instead of lmer(). However, when trying to run lmer1(), it will tell you this?warning message: Warning message: model.Matrix() has been moved from package 'Matrix' to the new package 'MatrixModels' which is now loaded (if installed). ? Its use from package 'Matrix' is deprecated. Do use it from 'MatrixModels' instead. I think this?may be?why I got error message when I try to load lme4a, which may have not been updated to look for MatrixModels package instead of Matrix package. The reason I posted to both R and R-mixed-models mailing list is that it seems that this question?is more suitable?to R-mixed-models, but response there is pretty slow,...... Thanks, John ? ----- Original Message ---- From: Gavin Simpson <gavin.simpson at ucl.ac.uk> To: array chip <arrayprofile at yahoo.com> Cc: John Sorkin <jsorkin at grecc.umaryland.edu>; r-help at r-project.org; Bert Gunter <gunter.berton at gene.com> Sent: Fri, September 10, 2010 10:46:16 AM Subject: Re: lme4a package loading error
On Fri, 2010-09-10 at 10:23 -0700, array chip wrote:
Thanks for reminding this. So I found lme4a package from Doug's UserR!2010 presentation folder: http://lme4.r-forge.r-project.org/slides/2010-07-20-Gaithersburg/pkg/
What is wrong with the one on the packages tab of the lme4 project page: https://r-forge.r-project.org/R/?group_id=60 ? You might need to make sure you have the latest Matrix as well to run lme4a. Update Matrix via update.packages() or install the latest version from r-forge and see if that helps. Also, try not to cross-post to multiple lists. Stick with one, or move the thread onto the new list. HTH G
However, after installation, I got the following error message when trying to load the library: library(Matrix)
library(Rcpp) library(minqa) library(lme4a)
Error : classes "modelMatrix", "denseModelMatrix", "sparseModelMatrix", "ddenseModelMatrix", "dsparseModelMatrix", "predModule", "dPredModule", "sPredModule", "respModule", "glmRespMod", "nlsRespMod" are not exported by 'namespace:Matrix' Error: package/namespace load failed for 'lme4a' Here is my sessionInfo()
sessionInfo()
R version 2.11.1 (2010-05-31) i386-pc-mingw32 locale: [1] LC_COLLATE=English_United States.1252? LC_CTYPE=English_United States.1252? [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C? ? ? ? ? ? ? ? ? ? ? ? ? [5] LC_TIME=English_United States.1252? ? attached base packages: [1] stats? ? graphics? grDevices utils? ? datasets? methods? base? ? other attached packages: [1] minqa_1.1.9? ? ? ? Rcpp_0.8.6? ? ? ? Matrix_0.999375-43 lattice_0.18-8? ? loaded via a namespace (and not attached): [1] grid_2.11.1? ? nlme_3.1-96? ? splines_2.11.1 stats4_2.11.1? tools_2.11.1? Any suggestions would be appreciated. John ----- Original Message ---- From: Gavin Simpson <gavin.simpson at ucl.ac.uk> To: array chip <arrayprofile at yahoo.com> Cc: John Sorkin <jsorkin at grecc.umaryland.edu>; r-help at r-project.org; Bert Gunter <gunter.berton at gene.com> Sent: Fri, September 10, 2010 10:00:15 AM Subject: Re: [R] lmer fixed effects, SE, t . . . and p On Fri, 2010-09-10 at 09:51 -0700, array chip wrote:
But as far as I know, profile() seems to be de-activated in the lme4
package.
It is beta software. The lme4a version of the lme4 "package" might have had profile re-enabled, IIRC. G
----- Original Message ---- From: Gavin Simpson <gavin.simpson at ucl.ac.uk> To: John Sorkin <jsorkin at grecc.umaryland.edu> Cc: r-help at r-project.org; Bert Gunter <gunter.berton at gene.com> Sent: Fri, September 10, 2010 2:05:37 AM Subject: Re: [R] lmer fixed effects, SE, t . . . and p On Thu, 2010-09-09 at 23:40 -0400, John Sorkin wrote:
Bert, I appreciate you comments, and I have read Doug Bates writing about p values in mixed effects regression. It is precisely because I read Doug's material that I asked "how are we to interpret the estimates" rather than "how can we compute a p value". My question is a simple question whose answer is undoubtedly complex, but one that needs an answer. Without p values, or confidence intervals, I am not certain what to make of the results of my analysis. Does my analysis suggest, or does it not suggest that there is a relation between time and y? If I can't answer this question after running the analysis, I don't have any more information than I did before I ran the analysis, and a fair question would be why did I run the analysis? I am asking for help not in calculation a p value or a CI, but rather to know what I can and can't say about the results of the analysis. If this basic question can not be answered, I am at a loss to interpret my results. Thank you, John
Doug talks quite a lot about profiling lmer fits using 'profile deviance' to investigate variability in fixed effects. For example, see section 1.5 in the draft of chapter 1 of Doug's book on mixed models: http://lme4.r-forge.r-project.org/book/ HTH G
John David Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics University of Maryland School of Medicine Division of Gerontology Baltimore VA Medical Center 10 North Greene Street GRECC (BT/18/GR) Baltimore, MD 21201-1524 (Phone) 410-605-7119 (Fax) 410-605-7913 (Please call phone number above prior to faxing)>>> Bert
Gunter <gunter.berton at gene.com> 9/9/2010 11:21 PM >>> John: Search on this issue in the list archives. Doug Bates has addressed it at length. Basically, he does not calculate CI's or p-values because he does not know how to reliably do so. However, the key remark in your query was:
(2) lmer does not give p values or confidence intervals for the fixed
effects. How we are to interpret the estimates given that no p value or CI
is
given for the estimates? Think about it. A statistical analysis -- ANY statistical analysis -- treats the data in isolation: it is not informed by physics, thermodynamics, biology,? other similar data, prior experience, or, indeed, any part of the body of relevant scientific knowledge. Do you really think that any such analysis, especially when predicated upon often tenuous or even (necessarily) unverifiable assumptions and simplifications should be considered authoritative? Classical statistical inference is just another piece of the puzzle, and not even particularly useful when, as if typically the case, hypotheses are formulated AFTER seeing the data (this invalidates the probability calculations -- hypotheses must be formulated before seeing the data to be meaningfully assessed). Leo Breiman called this statistics' "quiet scandal" something like 20 years ago, and he was no dummy. It is comforting, perhaps, but illusory to believe that statistical inference can be relied on to give sound, objective scientific results. True, without such a framework, science seems rather subjective, perhaps closer to religion and arbitrary cultural archetypes than we care to admit. But see Thomas Kuhn and Paul Feuerabend for why this is neither surprising nor necessarily a bad thing. Cheers, Bert Gunter On Thu, Sep 9, 2010 at 8:00 PM, John Sorkin <jsorkin at grecc.umaryland.edu> wrote:
windows Vista R 2.10.1 (1) How can I get the complete table of for the fixed effects from lmer.
As
can be seen from the example below, fixef(fit2) only give the estimates and
not
the SE or t value
fit3<- lmer(y~time + (1|Subject) +
(time|Subject),data=data.frame(data))
summary(fit3)
Linear mixed model fit by REML Formula: y ~ time + (1 | Subject) + (time | Subject) ? Data: data.frame(data) ? ? AIC? ? BIC logLik deviance REMLdev ? -126.2 -116.4? 70.1? -152.5? -140.2 Random effects: ? Groups? Name? ? ? ? Variance? Std.Dev.? Corr ? Subject? (Intercept) 2.9311e+01 5.41396385 ? Subject? (Intercept) 0.0000e+00 0.00000000 ? ? ? ? ? time? ? ? ? 0.0000e+00 0.00000000? NaN ? Residual? ? ? ? ? ? 8.1591e-07 0.00090328 Number of obs: 30, groups: Subject, 10 Fixed effects: ? ? ? ? ? ? Estimate Std. Error t value (Intercept) 14.998216? 1.712046? ? ? 9 time? ? ? ? -0.999779? 0.000202? -4950 Correlation of Fixed Effects: ? ? (Intr) time -0.001
fixef(fit3)
(Intercept)? ? ? ? time ? 14.9982158? -0.9997793 (2) lmer does not give p values or confidence intervals for the fixed
effects. How we are to interpret the estimates given that no p value or CI
is
given for the estimates?
John David Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)
Confidentiality Statement:
This email message, including any attachments, is for ...{{dropped:25}}
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