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Accounting for Complex Sample Designs in Analyses of the Survey of Consumer Finances
Author(s) -
Shin Su Hyun,
Hanna Sherman D.
Publication year - 2016
Publication title -
journal of consumer affairs
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.582
H-Index - 62
eISSN - 1745-6606
pISSN - 0022-0078
DOI - 10.1111/joca.12106
Subject(s) - estimator , statistics , ordinary least squares , econometrics , sample (material) , logistic regression , regression , mathematics , population , regression analysis , demography , chemistry , chromatography , sociology
We examined the effects of using bootstrap weights to account for the complex sample design in analyses of Survey of Consumer Finances ( SCF ) datasets. No article published in this journal that has used the SCF has mentioned the issue of complex sample designs. We compared results obtained without weights and with application of population and bootstrap weights in a logistic regression, and found no substantial differences between the unweighted and the weighted analyses. We also compared results for an ordinary least squares regression, and found few differences between unweighted and weighted models. Unweighted regressions produced more conservative significance tests than the counterpart, and some econometricians have suggested that unweighted analyses are better for hypothesis testing. If estimation of the magnitudes of effects is important, weighted regression may be better because it produces consistent estimators. Researchers should be cautious in drawing conclusions when weighted and unweighted effects are substantially different.