I have a set of data that is not normally distributed and for which I need to build a model. So, I tried the lrm function from the design-package. The first run went well, and I got the following results:
Wald Statistics Response: RVCL2PROC.mott Factor Chi-Square d.f. P TTV.mott (Factor+Higher Order Factors) 69.01 4 <.0001 All Interactions 12.13 3 0.0069 BEHANDLING (Factor+Higher Order Factors) 14.94 6 0.0208 All Interactions 12.13 3 0.0069 TTV.mott * BEHANDLING (Factor+Higher Order Factors) 12.13 3 0.0069 TOTAL 69.76 7 <.0001 Now, how is it to be interpreted? Does it mean that the p-value for the interaction (TTV.mott*BEHANDLING) is 0.0069? And what does the "TOTAL" p-value signify? Then, I ran exactly the same script on another dataset and got the following error message: singular information matrix in lrm.fit (rank= 0 ). Offending variable(s): Error in est[z$pivot[nvi:(irank + 1)] - kint] : only 0's may be mixed with negative subscripts Does anyone know? I suspect that the first question is probably rather easy for you clever guys but I'm a statistics noob so... looking forward to your help. Martin Kellner ______________________________________________ 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.
