This study investigates longitudinal linking of dichotomous item responses across three time points, focusing on Haberman, Haebara, Stocking-Lord linking, and concurrent calibration under item parameter drift (IPD). Joint and chain linking are examined. Three simulation studies compared these methods under IPD and different linking designs. The first study assessed linking methods under sampling error and uniform IPD, showing Haberman joint linking minimized bias and root mean square error (RMSE), especially at larger sample sizes, while concurrent calibration was most accurate without IPD. The second study introduced two designs: using anchor items across all three time points or only adjacent items between consecutive time points. Without IPD, concurrent calibration remained most precise, while under uniform IPD, Haberman methods balanced bias and precision. The third study analyzed nonuniform IPD, finding Haberman chain linking achieved the best bias and RMSE performance. Overall, chain linking outperformed joint linking under IPD. Implications for analyzing longitudinal linking designs are discussed.
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