[R] lrm-function: Interpretation and error message

[Martin Kellner]

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