similar to: Reproducing SAS GLM in R

Displaying 6 results from an estimated 6 matches similar to: "Reproducing SAS GLM in R"

2005 Feb 23
1
H-F corr.: covariance matrix for interaction effect
Hi, I'm still not quite there with my H-F (G-G) correction code. I have it working for the main effects, but I just can't figure out how to do it for the effect interactions. The thing I really don't know (and can't find anything about) is how to calculate the covariance matrix for the interaction between the two (or even n) main factors. I've looked through some books
2005 Feb 23
1
H-F corr.: covariance matrix for interaction effect
Hi, I'm still not quite there with my H-F (G-G) correction code. I have it working for the main effects, but I just can't figure out how to do it for the effect interactions. The thing I really don't know (and can't find anything about) is how to calculate the covariance matrix for the interaction between the two (or even n) main factors. I've looked through some books
2005 Feb 18
1
Two-factorial Huynh-Feldt-Test
Hi, I'm currently working on porting some SAS scripts to R, and hence need to do the same calculation (and get the same results) as SAS in order to make the transition easier for users of the script. In the script, I'm dealing with a two-factorial repeated-measures anova. I'll try to give you a short overview of the setup: - two between-cell factors: facBetweenROI (numbering
2011 Apr 10
2
howto calculate column means in data frame
Long story short, I have a big iterative procedure that produces a long list of data.frames such as the one called "results" here. Is there an easy way to produce a similar list of data.frames comprised of the mean of each of the columns in results, such that it ends up like the one I've shown in "resultsmean" below? I've tried apply and lapply, still not got the
2008 Oct 09
2
Singular information matrix in lrm.fit
Hi R helpers, I'm fitting large number of single factor logistic regression models as a way to immediatly discard factor which are insignificant. Everything works fine expect that for some factors I get error message "Singular information matrix in lrm.fit" which breaks whole execution loop... how to make LRM not to throw this error and simply skip factors with singularity
2004 Jun 05
1
Crash in OSX (PR#6940)
Full_Name: Murray Pung Version: 1.9.0 OS: OSX Mac Submission from: (NULL) (134.148.20.33) Date/Time: 2004-06-05 12:32:30 +1000 OS Version: 10.3.4 (Build 7H63) Report Version: 2 Command: R.bin Path: /Library/Frameworks/R.framework/Resources/bin/R.bin Version: 1.9.0 (R 1.9.0) PID: 358 Thread: 0 Exception: EXC_BAD_ACCESS (0x0001) Codes: KERN_PROTECTION_FAILURE (0x0002) at