[R] lrm-function: Interpretation and error message

[Frank E Harrell Jr]

Martin Kellner wrote:
> 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?
>   
To understand all that, first make sure you understand all the 
parameters in the model - as printed when you print the fit object.  
Then get print.anova.Design to annotate the output to display exactly 
which parameters are being tested in each line:

a <- anova(fit)
print(a, which='subscripts') # or 'names' or 'dots'

> 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
>   
Please follow the posting guide and submit a small example that 
reproduces this problem.

Frank
> 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
>
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> and provide commented, minimal, self-contained, reproducible code.
>
>   


-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                     Department of Biostatistics   Vanderbilt University