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
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License
Abierto (Texto Completo)
Description
Summary: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