Local Dependence

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In some data designs, data are collected from the same persons more than once, or observations are collected on equivalent items. Consequently there is reason to suspect that local dependence exists in the data. What is its impact on the Rasch measures?

 

Local dependence usually squeezes or stretches the logit measures, but does not usually change cut-points much when they are expressed in raw-score terms.

 

Ida Marais suggests:

To avoid local dependence in measuring change from pre-test to post-test:

1.Create a random, "stacked" dataset, in which each patient only appears once, either at pre-test or post-test.  For instance, see FORMAT= example 7.
2.Run an initial Winsteps analysis and create item and step anchor files: IFILE=if.txt, SFILE=sf.txt
3.Run Winsteps on the full pre-test data set using the IAFILE=if.txt and SAFILE=sf.txt from step #2
4.Run Winsteps on the full post-test data set using the IAFILE-if.txt and SAFILE=sf.txt from step #2

 

Marais I. Response dependence and the measurement of change. J Appl Meas. 2009;10(1):17-29

 

You can determine the effect of local dependence by cross-plotting the measures from 3) and 4) against the measures from an unanchored stacked analysis of all the data.

 

 

Here is an experiment to determine whether local dependence is a problem.

 

Assuming that data from the same persons may be a problem, select from your cases one of each different response string. This will make the data as heterogeneous as possible. Perform an analysis of this data set and see if that changes your conclusions markedly. If it does, then local dependence may be a concern. If it doesn't then local dependence is having no substantive impact.

 

Using Excel, a method of obtaining only one of each different response string:

 

0. Import the data into excel as a "character" column

1. from the Excel data pull down menu choose -> filter -> advanced filter

2. under "action" choose "copy to another location"

3. click "list range" and highlight the range of element numbers - if you want the whole column click on the letter at the top of the column

4. click "copy to" and choose an empty column, e.g., column J.

5. click "unique records only"

6. click "OK"

7. look at column J. The data are unique.