UNLABELLED: Unit non-response is a growing problem in sample surveys that can bias survey estimates if respondents and non-respondents differ systematically. OBJECTIVES: To compare the results of two nonresponse adjustment methods: field substitution and weighting nonresponse adjustment based on response propensity. METHODS: Field substitution and response propensity weights are used to adjust for non-response and their effect on the prevalence of six survey outcomes is compared. RESULTS: Although significant differences are found between respondents and non-respondents, only slight changes on prevalence estimates are observed after adjustment, with both techniques showing similar results. In the sole case of smoking, substitution seems to have further biased survey estimates. CONCLUSIONS: Our results suggest that when there is information available for both respondents and non-respondents, or if a careful sample substitution process is performed, weighting adjustments based on response propensity and field substitution produce comparable results on prevalence estimates.
UNLABELLED: Unit non-response is a growing problem in sample surveys that can bias survey estimates if respondents and non-respondents differ systematically. OBJECTIVES: To compare the results of two nonresponse adjustment methods: field substitution and weighting nonresponse adjustment based on response propensity. METHODS: Field substitution and response propensity weights are used to adjust for non-response and their effect on the prevalence of six survey outcomes is compared. RESULTS: Although significant differences are found between respondents and non-respondents, only slight changes on prevalence estimates are observed after adjustment, with both techniques showing similar results. In the sole case of smoking, substitution seems to have further biased survey estimates. CONCLUSIONS: Our results suggest that when there is information available for both respondents and non-respondents, or if a careful sample substitution process is performed, weighting adjustments based on response propensity and field substitution produce comparable results on prevalence estimates.
Authors: Johan Van der Heyden; Stefaan Demarest; Koen Van Herck; Dirk De Bacquer; Jean Tafforeau; Herman Van Oyen Journal: Int J Public Health Date: 2013-04-26 Impact factor: 3.380
Authors: Sara Fernández Sánchez-Escalonilla; Carlos Fernández-Escobar; Miguel Ángel Royo-Bordonada Journal: Int J Environ Res Public Health Date: 2022-03-22 Impact factor: 3.390
Authors: Cristina Cavero Esponera; Sara Fernández Sánchez-Escalonilla; Miguel Ángel Royo-Bordonada Journal: Int J Environ Res Public Health Date: 2022-07-13 Impact factor: 4.614