Cargando…

Biased sampling, over-identified parameter problems and beyond

This book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Econ...

Descripción completa

Detalles Bibliográficos
Autor principal: Qin, Jing
Lenguaje:eng
Publicado: Springer 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-981-10-4856-2
http://cds.cern.ch/record/2272831
_version_ 1780954959546679296
author Qin, Jing
author_facet Qin, Jing
author_sort Qin, Jing
collection CERN
description This book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Economics. The book addresses a range of important topics, including case and control studies, causal inference, missing data problems, meta-analysis, renewal process and length biased sampling problems, capture and recapture problems, case cohort studies, exponential tilting genetic mixture models etc. The goal of this book is to make it easier for Ph. D students and new researchers to get started in this research area. It will be of interest to all those who work in the health, biological, social and physical sciences, as well as those who are interested in survey methodology and other areas of statistical science, among others. .
id cern-2272831
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2017
publisher Springer
record_format invenio
spelling cern-22728312021-04-21T19:09:14Zdoi:10.1007/978-981-10-4856-2http://cds.cern.ch/record/2272831engQin, JingBiased sampling, over-identified parameter problems and beyondMathematical Physics and MathematicsThis book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Economics. The book addresses a range of important topics, including case and control studies, causal inference, missing data problems, meta-analysis, renewal process and length biased sampling problems, capture and recapture problems, case cohort studies, exponential tilting genetic mixture models etc. The goal of this book is to make it easier for Ph. D students and new researchers to get started in this research area. It will be of interest to all those who work in the health, biological, social and physical sciences, as well as those who are interested in survey methodology and other areas of statistical science, among others. .Springeroai:cds.cern.ch:22728312017
spellingShingle Mathematical Physics and Mathematics
Qin, Jing
Biased sampling, over-identified parameter problems and beyond
title Biased sampling, over-identified parameter problems and beyond
title_full Biased sampling, over-identified parameter problems and beyond
title_fullStr Biased sampling, over-identified parameter problems and beyond
title_full_unstemmed Biased sampling, over-identified parameter problems and beyond
title_short Biased sampling, over-identified parameter problems and beyond
title_sort biased sampling, over-identified parameter problems and beyond
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-981-10-4856-2
http://cds.cern.ch/record/2272831
work_keys_str_mv AT qinjing biasedsamplingoveridentifiedparameterproblemsandbeyond