The effects of three amounts of DIF (10%, 15 % and 30 % of DIF-items), three test lengths (20-, 40-, and 60-items), and three test score (matching criterion) purification types (single-stage, two-stage, and iterative) on robustness and power of Mantel-Haenszel (MH) DIF detection procedures were studied. Item response data were generated under the three parameter logistic model (3PLM) for focal and reference group subjects, where the ability distributions of the two groups were equal. In the 10% DIF item conditions the three MH procedures are robust and have sufficient power, but in the 15 % and 30 % DIF item conditions robustness violation and insufficient powers occur. The influence of test length on power is rather modest. On the other ha...
The standard Mantel-Haenszel (MH) procedure, a simple modification of the MH procedure (reanalyzing ...
grantor: University of TorontoModern bias detection procedures search for differences in i...
grantor: University of TorontoModern bias detection procedures search for differences in i...
The Mantel-Haenszel (MH) procedure is commonly used to detect items that function differentially for...
The standard Mantel-Haenszel (MH) procedure, a simple modification of the MH procedure (reanalyzing ...
The frequent use of standardized tests for admission, advancement, and accreditation has increased p...
The Mantel-Haenszel (MH) procedure has emerged as one of the methods of choice for identification of...
Sample-size restrictions limit the contingency table approaches based on asymptotic dis-tributions, ...
In recent years, public attention has become focused on the issue of test and item bias in standardi...
Two nonparametric procedures for detecting differ-ential item functioning (DIF)—the Mantel...
The Mantel-Haenszel (MH) procedure has become one of the most popular procedures for detecting diffe...
functioning [DIF] detection method, purification procedure, item response model, mean latent trait d...
Test-item bias has become an increasingly challenging investigation in statistics and education. A p...
Two nonparametric procedures for detecting differential item functioning (DIF)-the Mantel-Haenszel ...
Numerous statistical methods have been proposed for detecting differential item functioning (DIF). A...
The standard Mantel-Haenszel (MH) procedure, a simple modification of the MH procedure (reanalyzing ...
grantor: University of TorontoModern bias detection procedures search for differences in i...
grantor: University of TorontoModern bias detection procedures search for differences in i...
The Mantel-Haenszel (MH) procedure is commonly used to detect items that function differentially for...
The standard Mantel-Haenszel (MH) procedure, a simple modification of the MH procedure (reanalyzing ...
The frequent use of standardized tests for admission, advancement, and accreditation has increased p...
The Mantel-Haenszel (MH) procedure has emerged as one of the methods of choice for identification of...
Sample-size restrictions limit the contingency table approaches based on asymptotic dis-tributions, ...
In recent years, public attention has become focused on the issue of test and item bias in standardi...
Two nonparametric procedures for detecting differ-ential item functioning (DIF)—the Mantel...
The Mantel-Haenszel (MH) procedure has become one of the most popular procedures for detecting diffe...
functioning [DIF] detection method, purification procedure, item response model, mean latent trait d...
Test-item bias has become an increasingly challenging investigation in statistics and education. A p...
Two nonparametric procedures for detecting differential item functioning (DIF)-the Mantel-Haenszel ...
Numerous statistical methods have been proposed for detecting differential item functioning (DIF). A...
The standard Mantel-Haenszel (MH) procedure, a simple modification of the MH procedure (reanalyzing ...
grantor: University of TorontoModern bias detection procedures search for differences in i...
grantor: University of TorontoModern bias detection procedures search for differences in i...