Some items are more closely related than others. Comprehension items that address the same written text and arithmetic items requiring the same operation are examples. In Rasch analysis, this is no major source for concern provided there is no extreme systematic dependency between two or a few items. When such dependency does exist, combining the separate items into one partial-credit item may be useful. Low values of the Rasch INFIT statistic signal dependency. When a diagnostically specific investigation of inter-item dependency is required, Fisher's Z is useful.
1)Obtain the Rasch-based standardized residuals for each observation of Person n on item i:
zni = (Observedni - Expectedni)/Standard Errorni
2)Correlate the standardized residuals for all pairs of items i, j across all N persons:
rij = (sum(zni znj) - sum(zni)sum(znj)/N) / N SD(zni) SD(znj)
3)Use Fisher's Z to linearize Pearson correlations:
Zij = 1/2 Loge( (1+rij)/(1-rij) )
4)Draw a histogram of the Fisher Z values. Noticeable positive skew (see Figures) indicates the presence of sets of dependent items. A cluster analysis of the Z matrix will identify the sets. Outlying positive Z values flag pairs or sets of highly dependent items for further investigation.
Quantifying item dependency. Shen L. Rasch Measurement Transactions, 1996, 10:1 p.485
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