[R] fwdmsa package: Error in search.normal(X[samp, ], verbose = FALSE) : At least one item has no variance

Rob Cassidy rob.cassidy at concordia.ca
Wed Mar 21 20:54:37 CET 2012


I'm using the fwdmsa package to identify deviant cases in a Mokken scale
analysis. I've run into a problem., separate from the one I posted
previously. The problem comes with items that are "easy" by IRT standards. A
good scale should include a range of difficulties; yet when I include "easy"
items in a forward search I continuously run into the problem that these
items demonstrate no variability in the smaller subsamples selected for
forward search. I can resolve the problem by only running the analysis
without the easier items, but this is not ideal for for the analysis. 

The data are 150 responses to a 37 item test. For the first 15 items, they
look like this (the variable names are cumbersome and so have been removed)
: 
> head(by364.data) 
        
1        1    1    1    0    1    0    1    1    0    1    0    1    1    1   
1 
2        1    1    1    0    1    1    1    1    1    1    0    0    1    1   
1 
3        0    1    1    1    0    0    1    0    1    1    1    0    1    1   
0 
4        1    1    1    0    0    1    1    1    1    1    1    1    0    1   
1 
5        1    1    1    1    0    1    0    1    1    1    1    0    1    1   
0 
6        1    1    1    1    1    1    1    1    1    1    1    1    1    1   
1 


You can see that items 1, 2, 9 and 13 demonstrate no variance in this small
sample and thus muck up the analysis. This happens even when I have items
with plenty  of variance, but seeing as they are easy items, they might have
a .8 - .9 probability of endorsement, so even in samples of 25-50, still run
into this variance problem.  I have seeded the forward search with specific
cases that create the necessary variance, but these artificial subsamples
tend to loaded with deviant observations and thus are excluded after a
couple of steps, creating the lack of variance problem. 

Any suggestions? 

Robert 

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