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            Multilevel Analysis

            A Pratical Introduction

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            Download Url(s)
            https://books.openedition.org/ined/17717
            Author(s)
            Bringé, Arnaud
            Golaz, Valérie
            Contributor(s)
            Reeve, Paul (other)
            Language
            English
            Show full item record
            Abstract
            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.
            URI
            https://directory.doabooks.org/handle/20.500.12854/85502
            Keywords
            demography; quantitative data; study of populations; computing; statistical methodology; multilevel
            DOI
            10.4000/books.ined.17717
            Webshop link
            https://www.7switch.com/fr/ebo ...
            ISBN
            9782733290538
            Publisher
            Ined Éditions
            Publisher website
            https://books.openedition.org/ined
            Publication date and place
            Paris, 2022
            Series
            Méthodes et Savoirs,
            Classification
            Population and demography
            Rights
            https://www.openedition.org/6540?lang=en
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            Credits


            • logo Investir l'avenirInvestir l'avenir
            • logo MESRIMESRI
            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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