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Transitioning a panel survey from in‐person to predominantly web data collection : Results and lessons learned

Biemer, Paul P.; Harris, Kathleen Mullan; Burke, Brian J.; … - In: Journal of the Royal Statistical Society: Series A … 185 (2021) 3, pp. 798-821

Persistent link: https://www.econbiz.de/10012636983

Study design and methods

Biemer, Paul P.; Dowd, Kathryn; Webb, Mary Bruce - In: Child welfare and child well-being : new perspectives …, (pp. 3-50). 2010

Persistent link: https://www.econbiz.de/10003982714

Latent classification of physical abuse as a predictor of adolescent functioning

Izzo, Charles V.; Smith, Elliot G.; Eckenrode, John J.; … - In: Child welfare and child well-being : new perspectives …, (pp. 107-132). 2010

Persistent link: https://www.econbiz.de/10003982751

An application of bootstrapping for determining a decision rule for site location

Biemer, Paul P. - In: Journal of business & economic statistics : JBES ; a … 9 (1991) 2, pp. 189-196

Persistent link: https://www.econbiz.de/10001104137

The optimal design of quality control samples to detect interviewer cheating

Biemer, Paul P. - In: Journal of official statistics : JOS ; an international … 5 (1989) 1, pp. 23-39

Persistent link: https://www.econbiz.de/10001068583

Measurement errors in sample surveys

Biemer, Paul P. - 2009

Persistent link: https://www.econbiz.de/10003878875

Using level-of-effort paradata in non-response adjustments with application to field surveys

Biemer, Paul P.; Chen, Patrick; Wang, Kevin - In: Journal of the Royal Statistical Society Series A 176 (2013) 1, pp. 147-168

Persistent link: https://www.econbiz.de/10010642768

Introduction to survey quality

Biemer, Paul P.; Lyberg, Lars - 2003

Persistent link: https://www.econbiz.de/10004769163

Measurement error evaluation of self-reported drug use: a latent class analysis of the US National Household Survey on Drug Abuse

Biemer, Paul P.; Wiesen, Christopher - In: Journal of the Royal Statistical Society Series A 165 (2002) 1, pp. 97-119

Persistent link: https://www.econbiz.de/10005186975

Local Dependence in Latent Class Analysis of Rare and Sensitive Events

Berzofsky, Marcus E.; Biemer, Paul P.; Kalsbeek, William D. - In: Sociological Methods & Research 43 (2014) 1, pp. 137-170

For survey methodologists, latent class analysis (LCA) is a powerful tool for assessing the measurement error in survey questions, evaluating survey methods, and estimating the bias in estimates of population prevalence. LCA can be used when gold standard measurements are not available and...

Persistent link: https://www.econbiz.de/10010789508