The Impact of Using Incorrect Weights With the Multiple Membership Random Effects Model

Abstract

The multiple membership random effects model (MMREM) is used to appropriately model multiple membership data structures. Use of the MMREM requires selection of weights reflecting the hypothesized contribution of each level two unit (e.g., school) and their descriptors to the level one outcome. This study assessed the impact on MMREM parameter and residual estimates of the choice of weight pattern used. Parameter and residual estimates resulting from use of different weight patterns were compared using a real dataset and a small-scale simulation study. Under the conditions examined here, results indicated that choice of weight pattern did not greatly impact relative parameter bias nor level two residuals’ ranks. Limitations and directions for future research are discussed.