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The Impact of Missing Background Data on Subpopulation Estimation
Author(s) -
Rutkowski Leslie
Publication year - 2011
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/j.1745-3984.2011.00144.x
Subject(s) - missing data , statistics , econometrics , population , estimation , point estimation , mathematics , demography , economics , management , sociology
Although population modeling methods are well established, a paucity of literature appears to exist regarding the effect of missing background data on subpopulation achievement estimates. Using simulated data that follows typical large‐scale assessment designs with known parameters and a number of missing conditions, this paper examines the extent to which missing background data impacts subpopulation achievement estimates. In particular, the paper compares achievement estimates under a model with fully observed background data to achievement estimates for a variety of missing background data conditions. The findings suggest that sub‐population differences are preserved under all analyzed conditions while point estimates for subpopulation achievement values are influenced by missing at random conditions. Implications for cross‐population comparisons are discussed.