Title: A comparison of procedures for handling mobility and missing level-2 identifiers in two-level data
Authors: Lindsey J. Wolff Smith; S. Natasha Beretvas
Addresses: Department of Statistics and Data Sciences, The University of Texas at Austin, 1 University Station, G2500, Austin, Texas 78712, USA ' Educational Psychology Department, The University of Texas at Austin, 1 University Station, D5800, Austin, Texas 78712, USA
Abstract: This simulation study compared three ad hoc procedures for handling mobility of level-1 units across level-2 units and handling missing level-2 (here, school) identifiers for some level-1 units (students). The HLM-Delete procedure used the conventional hierarchical linear model (HLM) to analyse a dataset from which mobile and missing-identifier students had been removed. The MMREM-Delete procedure involved removing only students who were missing level-2 identifiers and estimating a multiple membership random effects model (MMREM). The third procedure (MMREM-Unique) involved no deletion and entailed creation of a pseudo-identifier for each missing level-2 identifier. All three procedures omitted a predictor of mobility from the estimating model. To provide a baseline comparison, a correctly specified MMREM was also estimated. Relative parameter bias was calculated for each parameter estimated. Across conditions, each procedure had some level of substantial bias with HLM-Delete performing worst. Results and implications for applied researchers are discussed.
Keywords: student mobility; multilevel models; hierarchical linear models; HLM; missing data; multiple membership random effects model; MMREM; modelling; two-level data; simulation; elementary education; elementary schools.
International Journal of Quantitative Research in Education, 2014 Vol.2 No.2, pp.153 - 174
Available online: 19 Aug 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article