CUTHI= cut off responses with high expectations = 0 logits, no

Use this if careless responses are evident. CUTHI= cuts off the top left-hand corner of the Scalogram in Table 22.

 

Eliminates (cuts off) observations where examinee ability measure is CUTHI= logits or more higher than item difficulty measure, so the examinee has a high probability of success. Removing off-target responses takes place after PROX has converged. After elimination, PROX is restarted, followed by JMLE estimation and fit calculation using only the reduced set of responses. This may mean that the original score-based ordering is changed.

 

Usually with CUTLO= and CUTHI=, misfitting items aren't deleted - but miskeys etc. must be corrected first. Setting CUTLO= and CUTHI= is a compromise between fit and missing data. If you loose too much data, then increase the values. If there is still considerable misfit or skewing of equating, then decrease the values.

 

Here are the usual effects of CUTLO= and CUTHI=

1. Fit to the Rasch model improves.

2. The count of observations for each person and item decreases.

3. The variance in the data explained by the measures decreases.

 

Polytomous items: CUTLO= and CUTHI= trim the data relative to the item difficulty, so they tend to remove data in high and low categories. You can adjust the item difficulty relative to the response structure using SAFILE=.

 

Example 1: Eliminate responses where examinee measure is 3 or more logits higher than item measure, to eliminate their worst careless wrong responses:

CUTHI= 3

 

 This produces a scalogram with eliminated responses blanked out:: Table 22

 

  RESPONSES SORTED BY MEASURE:

  KID    TAP

                111111111

       123745698013245678

  ------------------------                        

   15  111       11100000 observations for extreme scores remain

   14  111     1110000000

   28  111   111010000000

   30  1111 1111000000000

   27  111111100000000000

 

Example 2. At www.rasch.org/rmt/rmt62a.htm the originator of this approach suggests CUTLO= -1 and CUTHI=2