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Multilevel Analysis. A Pratical Introduction
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- FormatMulti-format
- ISBN978-2-7332-9053-8
- EAN9782733290538
- Date de parution17/02/2022
- Protection num.NC
- Infos supplémentairesMulti-format incluant PDF avec W...
- ÉditeurIned Éditions via OpenEdition
Résumé
Demographers describe and analyse individual events at multiple levels of observation that range from the individuals themselves to the overall population of interest. In quantitative population studies, one way to streamline investigation is to perform a multilevel statistical analysis using a single model, which improves the accuracy of the estimates and therefore of the results. To that end, this book guides the reader through the first stages of multilevel analysis, from design to implementation, with step-by-step explanations on how to navigate the three most common statistical software environments (Stata®, SAS®, and R).
Concrete examples based on census data are provided using an analysis of school enrolment in rural Kenya. Intended for all statistical database users seeking to develop or expand their knowledge of multilevel analysis, this manual details and illustrates the procedures for creating multilevel models and discusses their prerequisites, advantages, and limitations. Suggestions for further reading are also provided.
Concrete examples based on census data are provided using an analysis of school enrolment in rural Kenya. Intended for all statistical database users seeking to develop or expand their knowledge of multilevel analysis, this manual details and illustrates the procedures for creating multilevel models and discusses their prerequisites, advantages, and limitations. Suggestions for further reading are also provided.
Demographers describe and analyse individual events at multiple levels of observation that range from the individuals themselves to the overall population of interest. In quantitative population studies, one way to streamline investigation is to perform a multilevel statistical analysis using a single model, which improves the accuracy of the estimates and therefore of the results. To that end, this book guides the reader through the first stages of multilevel analysis, from design to implementation, with step-by-step explanations on how to navigate the three most common statistical software environments (Stata®, SAS®, and R).
Concrete examples based on census data are provided using an analysis of school enrolment in rural Kenya. Intended for all statistical database users seeking to develop or expand their knowledge of multilevel analysis, this manual details and illustrates the procedures for creating multilevel models and discusses their prerequisites, advantages, and limitations. Suggestions for further reading are also provided.
Concrete examples based on census data are provided using an analysis of school enrolment in rural Kenya. Intended for all statistical database users seeking to develop or expand their knowledge of multilevel analysis, this manual details and illustrates the procedures for creating multilevel models and discusses their prerequisites, advantages, and limitations. Suggestions for further reading are also provided.
