A Two-Stage Multilevel Randomized Response Technique with Proportional Odds Models and Missing Covariates

Autor/inn/en	Hsieh, Shu-Hui; Lee, Shen-Ming; Li, Chin-Shang
Titel	A Two-Stage Multilevel Randomized Response Technique with Proportional Odds Models and Missing Covariates
Quelle	In: Sociological Methods & Research, 51 (2022) 1, S.439-467 (29 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Hsieh, Shu-Hui) ORCID (Lee, Shen-Ming)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0049-1241
DOI	10.1177/0049124120914954
Schlagwörter	Income; Surveys; Response Rates (Questionnaires); Response Style (Tests); Privacy; Foreign Countries; Bias; Taiwan + Suchen Sie Ihr Suchwort? Einkommen; Survey; Umfrage; Befragung; Antwortkontrolle; Antwortverhalten; Privatsphäre; Ausland
Abstract	Surveys of income are complicated by the sensitive nature of the topic. The problem researchers face is how to encourage participants to respond and to provide truthful responses in surveys. To correct biases induced by nonresponse or underreporting, we propose a two-stage multilevel randomized response (MRR) technique to investigate the true level of income and to protect personal privacy. For a wide range of applications, we present a proportional odds model for two-stage MRR data and apply inverse probability weighting and multiple imputation methods to deal with covariates on some subjects that are missing at random. A simulation study is conducted to investigate the effects of missing covariates and to evaluate the performance of the proposed methods. The practicality of the proposed methods is illustrated with the regular monthly income data collected in the Taiwan Social Change Survey. Furthermore, we provide an estimate of personal regular monthly mean income. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01