{"product_id":"multilevel-modeling-in-plain-language-9780857029157","title":"Multilevel Modeling in Plain Language","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eHave you been told you need to do multilevel modeling, but you can't get past the forest of equations? Do you need the techniques explained with words and practical examples so they make sense?\u003c\/p\u003e  \u003cp\u003eHelp is here! This book unpacks these statistical techniques in easy-to-understand language with fully annotated examples using the statistical software Stata. The techniques are explained without reliance on equations and algebra so that new users will understand when to use these approaches and how they are really just special applications of ordinary regression. Using real life data, the authors show you how to model random intercept models and random coefficient models for cross-sectional data in a way that makes sense and can be retained and repeated.\u003cbr\u003e  \u003cbr\u003e  This book is the perfect answer for anyone who needs a clear, accessible introduction to multilevel modeling.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eI started to read the book with vivid interest because of the subject that too often does not find enough space in books which provide an overview of the most used statistical methods  leaving out those who are somewhat a little bit more elaborate. After a while I found that I had read many pages, as a story, in a short time, and, rethinking to the title of the book, I remembered there was a part saying \"…. In plain language\". This is really genuine. \u003cbr\u003e \u003cbr\u003e The Authors do really introduce the subject in a very friendly way, propose examples which facilitate the reader to better  understand and explain the output of Stata.  I suggest the book both to students and instructors who want a specific text on this subject. On the one hand, students will be not afraid of formula, considering that the book is centred on the understanding of the subjects, on the other hand, instructors will benefit in reviewing the path of the multilevel analysis very quickly. \u003cbr\u003e \u003cbr\u003e It is a book for those who have some knowledge of statistic but I think that this aspect is definitely clear to the reader. The book is really complete in all the phases of a multilevel analysis, the \"plain approach\" helps the reader to grasp the idea,  follow the Stata commands and outputs and, finally, to interpret the findings. I think that the Authors were very skillful in preparing this book and added a very useful resource, in particular, for those who use Stata for their analysis.\u003c\/p\u003e -- Dr. Gabriele Messina\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eChapter 1: What Is Multilevel Modeling and Why Should I Use It?    Mixing levels of analysis    Theoretical reasons for multilevel modeling    What are the advantages of using multilevel models?    Statistical reasons for multilevel modeling    Assumptions of OLS    Software    How this book is organized Chapter 2: Random Intercept Models: When intercepts vary    A review of single-level regression    Nesting structures in our data    Getting starting with random intercept models    What do our findings mean so far?    Changing the grouping to schools    Adding Level 1 explanatory variables    Adding Level 2 explanatory variables    Group mean centring    Interactions    Model fit    What about R-squared?    R-squared?    A further assumption and a short note on random and fixed effects Chapter 3: Random Coefficient Models: When intercepts and coefficients vary    Getting started with random coefficient models    Trying a different random coefficient    Shrinkage    Fanning in and fanning out    Examining the variances    A dichotomous variable as a random coefficient    More than one random coefficient    A note on parsimony and fitting a model with multiple random coefficients    A model with one random and one fixed coefficient    Adding Level 2 variables    Residual diagnostics    First steps in model-building    Some tasters of further extensions to our basic models    Where to next? Chapter 4: Communicating Results to a Wider Audience    Creating journal-formatted tables    The fixed part of the model    The importance of the null model    Centring variables    Stata commands to make table-making easier    What do you talk about?    Models with random coefficients    What about graphs?    Cross-level interactions    Parting words","brand":"SAGE Publications Ltd","offers":[{"title":"Default Title","offer_id":51768261083479,"sku":"9780857029157","price":999.99,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780857029157.jpg?v=1758717103","url":"https:\/\/bookcurl.com\/products\/multilevel-modeling-in-plain-language-9780857029157","provider":"Book Curl","version":"1.0","type":"link"}