Multilevel modelling for public health and health services research : health in context

This book is designed as a practical introduction to multilevel analysis (MLA). It is borne out of a course that we have taught over the past 20 years for an international audience of public health and health services researchers of varied statistical ability. The practical side of the book is in th...

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Autores:
Tipo de recurso:
Book
Fecha de publicación:
2020
Institución:
Universidad de Bogotá Jorge Tadeo Lozano
Repositorio:
Expeditio: repositorio UTadeo
Idioma:
eng
OAI Identifier:
oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/15906
Acceso en línea:
http://hdl.handle.net/20.500.12010/15906
https://doi.org/10.1007/978-3-030-34801-4
Palabra clave:
Public Health
Health Services Research
Ciencias sociales
Salud pública
Asistencia médica
Rights
License
Abierto (Texto Completo)
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dc.title.spa.fl_str_mv Multilevel modelling for public health and health services research : health in context
title Multilevel modelling for public health and health services research : health in context
spellingShingle Multilevel modelling for public health and health services research : health in context
Public Health
Health Services Research
Ciencias sociales
Salud pública
Asistencia médica
title_short Multilevel modelling for public health and health services research : health in context
title_full Multilevel modelling for public health and health services research : health in context
title_fullStr Multilevel modelling for public health and health services research : health in context
title_full_unstemmed Multilevel modelling for public health and health services research : health in context
title_sort Multilevel modelling for public health and health services research : health in context
dc.subject.spa.fl_str_mv Public Health
Health Services Research
topic Public Health
Health Services Research
Ciencias sociales
Salud pública
Asistencia médica
dc.subject.lemb.spa.fl_str_mv Ciencias sociales
Salud pública
Asistencia médica
description This book is designed as a practical introduction to multilevel analysis (MLA). It is borne out of a course that we have taught over the past 20 years for an international audience of public health and health services researchers of varied statistical ability. The practical side of the book is in the use of the data sets that are supplied with the book. The book contains full guidance for the analysis of these real-life data sets. The level of statistical sophistication that we expect from the readership is what we usually found among early stage PhD researchers in the health and healthcare field: a basic understanding of ordinary least squares and logistic regression. This is not to say that our target audience is restricted to PhD researchers; anyone who has discovered the need for MLA in health research with these basic statistical skills should be able to benefit from this book. The contents of the book are divided into four parts. The first part introduces the theoretical, conceptual and methodological background to MLA (Chaps. 1–4). The second part is devoted to the statistical background (Chaps. 5 and 6). Part III takes the final step towards application as we discuss aspects of the modelling process and pay attention to the presentation of research that uses MLA (Chaps. 7–10). With Part IV, we move to practical applications using example data sets. This part also introduces and discusses the use of MLwiN, the statistical package that is used with the example data sets. We work through three example data sets and introduce readers to the use of the software and the application of the ideas discussed in the previous chapters (Chaps. 11–13). Our suggested use of this book is as part of the learning process for health researchers, whether this is through formal teaching (Chaps. 1–10 can be thought of as a series of lectures with Chaps. 11–13 forming the basis of practical work) or through self-training. Either way we would urge the user to work through all chapters sequentially. Throughout the book we refer to further sources of information, whether these relate to the methodology introduced or to substantive examples or applications. This should further assist the users in the contextualisation of their own research. We advise readers to download and read articles that relate to examples that they find interesting
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-11-23T14:07:47Z
dc.date.available.none.fl_str_mv 2020-11-23T14:07:47Z
dc.date.created.none.fl_str_mv 2020
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format http://purl.org/coar/resource_type/c_2f33
dc.identifier.isbn.none.fl_str_mv 978-3-030-34801-4
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12010/15906
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1007/978-3-030-34801-4
identifier_str_mv 978-3-030-34801-4
url http://hdl.handle.net/20.500.12010/15906
https://doi.org/10.1007/978-3-030-34801-4
dc.language.iso.spa.fl_str_mv eng
language eng
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.local.spa.fl_str_mv Abierto (Texto Completo)
dc.rights.creativecommons.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv Abierto (Texto Completo)
http://creativecommons.org/licenses/by/4.0/
http://purl.org/coar/access_right/c_abf2
dc.format.extent.spa.fl_str_mv 293 páginas
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Springer
institution Universidad de Bogotá Jorge Tadeo Lozano
bitstream.url.fl_str_mv https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/15906/2/license.txt
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spelling 2020-11-23T14:07:47Z2020-11-23T14:07:47Z2020978-3-030-34801-4http://hdl.handle.net/20.500.12010/15906https://doi.org/10.1007/978-3-030-34801-4This book is designed as a practical introduction to multilevel analysis (MLA). It is borne out of a course that we have taught over the past 20 years for an international audience of public health and health services researchers of varied statistical ability. The practical side of the book is in the use of the data sets that are supplied with the book. The book contains full guidance for the analysis of these real-life data sets. The level of statistical sophistication that we expect from the readership is what we usually found among early stage PhD researchers in the health and healthcare field: a basic understanding of ordinary least squares and logistic regression. This is not to say that our target audience is restricted to PhD researchers; anyone who has discovered the need for MLA in health research with these basic statistical skills should be able to benefit from this book. The contents of the book are divided into four parts. The first part introduces the theoretical, conceptual and methodological background to MLA (Chaps. 1–4). The second part is devoted to the statistical background (Chaps. 5 and 6). Part III takes the final step towards application as we discuss aspects of the modelling process and pay attention to the presentation of research that uses MLA (Chaps. 7–10). With Part IV, we move to practical applications using example data sets. This part also introduces and discusses the use of MLwiN, the statistical package that is used with the example data sets. We work through three example data sets and introduce readers to the use of the software and the application of the ideas discussed in the previous chapters (Chaps. 11–13). Our suggested use of this book is as part of the learning process for health researchers, whether this is through formal teaching (Chaps. 1–10 can be thought of as a series of lectures with Chaps. 11–13 forming the basis of practical work) or through self-training. Either way we would urge the user to work through all chapters sequentially. Throughout the book we refer to further sources of information, whether these relate to the methodology introduced or to substantive examples or applications. This should further assist the users in the contextualisation of their own research. 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