Message-ID: <AE8B81FD-D308-40EA-ABC8-2DB8293E9864@nih.gov>
Date: 2012-03-01T17:44:30Z
From: Joehanes, Roby (NIH/NHLBI) [F]
Subject: Bleeding edge lme4 (or lme4a) plus DF estimation
In-Reply-To: <CAO7JsnRJ+dsFkU_sYh-Eo=xR-RT7R5HLJdAWyMyqJr5qymAjyQ@mail.gmail.com>
Dr Bates,
Thank you for your reply.
I discovered a bug on your lme4Eigen's refit function. This is on version 0.9996875-9 (Description revision 169). I hope I got this right. If the original data matrix has some missing data in it, somehow the X and Z matrices (and y column) are correctly trimmed (i.e., the rows with missing data are removed). However, if I fit it with another y column, it reports error due to length mismatch. The error is as follows:
Error: length(newresp <- as.numeric(as.vector(newresp))) == length(rr$y) is not TRUE
Should I try the latest version and see if this bug has been fixed?
Also, will update method speed up computation if I changed the X (or Z) matrix a little bit by swapping or adding up to three columns (from about 40+ columns)?
Thank you,
Roby
On Feb 27, 2012, at 6:03 PM, Douglas Bates wrote:
> Yes, check out the refit function. I just saw that the documentation
> suffers from cut-and-paste errors but the general idea is to give a
> fitted model a new response and run only the optimization step.