Multi-level modelling in health research: a caution and rejoinder on temporally mismatched data.
In a review of the multilevel modelling literature (MLM) we find that data on individuals and their social environment contexts (neighbourhoods, municipalities) are often drawn from different years/time periods. This temporal mismatch has scarcely attracted any attention though it can significantly influence modelling results and interpretation. We demonstrate the influence of temporal mismatch first by outlining the degree of neighbourhood mobility in large metropolitan areas in Britain, Canada and the United States and second with a brief MLM example. We conclude that researchers ought to provide more study context when such mismatch is unavoidable.
Buzzelli
Michael
M
Department of Geography, University of British Columbia, 1984 West Mall, Vancouver, BC, Canada V6T 1Z2. buzzelli@geog.ubc.ca
Su
Jason
J
D015982:Bias; D002170:Canada; D003627:Data Interpretation, Statistical; D004812:Epidemiologic Methods; D006302:Health Services Research / Q000379:methods*; D006801:Humans; D011157:Population Dynamics / Q000706:statistics & numerical data*; D012931:Social Environment; D012959:Socioeconomic Factors; D013995:Time; D006113:United Kingdom; D014481:United States; D014505:Urban Population