The Effectiveness of Mantel Haenszel Log Odds Ratio Method in Detecting Differential Item Functioning Across Different Sample Sizes and Test Lengths Using Real Data Analysis

Objectives: This study aims to determine the effectiveness of the Mantel Haenszel Log Odds Ratio method in detecting Differential Item Functioning (DIF) across gender, while considering variations in sample size and test length. Utilizing real data, the study draws from a sample of tenth-grade students in Jordan who participated in the 2018 PISA International Mathematics Test. Methods: The study employs the experimental methodology, utilizing three levels of sample size and test length: (342, 200, and 100) and (30, 20, and 10), respectively. Nine iterations of the DDFS program were conducted to collect the results, representing nine scenarios resulting from the intersection of sample size and test length levels. Results: The study indicates that variations in sample size and test length significantly affect the Mantel-Hanzel (MH) method. Specifically, it observes an improvement in the MH method’s ability to detect DIF items with larger sample sizes, while maintaining a consistent test length. Conversely, the method’s efficacy declines with longer test lengths, despite maintaining a fixed sample size at a specific level. Conclusion: The study recommends using a large sample size and a short test length for effective detection of DIF items using the MH method.