02032    a2200325   4500001001400000003000800014005001700022007001500039008004000054020002200094024003400116040001500150041000800165100002100173245008800194260003700282500001000319520105800329540006501387650001501452650001501467650002201482650002501504650001401529650002801543650001501571700002101586856008401607999001501691OB-ined-17717FrMaCLE20251214082634.0cu ||||||m||||220216e||||||||xx |||||s|||||||||0|en|d  a978-2-7332-9053-87 a10.4000/books.ined.177172doi  aFR-FrMaCLE  aeng1 aBringé, Arnaud10aMultilevel Analysis :bA Pratical Introduction /cArnaud Bringé, Valérie Golaz.  aParis :bIned Éditions,c2022.  aEbook  a 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.  aOpenEdition Books Licenseuhttps://www.openedition.org/12554 4aDemography 4ademography 4aquantitative data 4astudy of populations 4acomputing 4astatistical methodology 4amultilevel1 aGolaz, Valérie4 eBringé, Arnauduhttps://books.openedition.org/ined/17717yMultilevel Analysis  c5723d5723