data analysis using regression and multilevel hierarchical models analytical methods for social research

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Data Analysis Using Regression And Multilevel Hierarchical Models

Author : Andrew Gelman
ISBN : 052168689X
Genre : Mathematics
File Size : 85. 90 MB
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This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

Data Analysis Using Regression And Multilevel Hierarchical Models

Author : Andrew Gelman
ISBN : 9781139460934
Genre : Mathematics
File Size : 62. 37 MB
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Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.

Data Analysis Using Regression And Multilevel Hierarchical Models

Author : Andrew Gelman
ISBN : 0521867061
Genre : Mathematics
File Size : 36. 66 MB
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This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

Hierarchical Linear Models

Author : Stephen W. Raudenbush
ISBN : 076191904X
Genre : Mathematics
File Size : 89. 39 MB
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Popular in its first edition for its rich, illustrative examples and lucid explanations of the theory and use of hierarchical linear models (HLM), the book has been updated to include: an intuitive introductory summary of the basic procedures for estimation and inference used with HLM models that only requires a minimal level of mathematical sophistication; a new section on multivariate growth models; a discussion of research synthesis or meta-analysis applications; aata analytic advice on centering of level-1 predictors, and new material on plausible value intervals and robust standard estimators.

Event History Modeling

Author : Janet M. Box-Steffensmeier
ISBN : 0521546737
Genre : Political Science
File Size : 40. 51 MB
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Event History Modeling provides an accessible, up-to-date guide to event history analysis for researchers and advanced students in the social sciences. The authors explain the foundational principles of event-history analysis, and analyse numerous examples which they estimate and interpret using standard statistical packages, such as STATA and S-Plus. They review recent and critical innovations in diagnostics, including testing the proportional hazards assumption, identifying outliers, and assessing model fit. They also discuss common problems encountered with time-to-event data, and make recommendations regarding the implementation of duration modeling methods.

Regression Models For Categorical And Limited Dependent Variables

Author : J. Scott Long
ISBN : 0803973748
Genre : Mathematics
File Size : 47. 67 MB
Format : PDF
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A unified treatment of the most useful models for categorical and limited dependent variables (CLDVs) is provided in this book. Throughout, the links among the models are made explicit, and common methods of derivation, interpretation and testing are applied. In addition, the author explains how models relate to linear regression models whenever possible.

Multilevel Analysis For Applied Research

Author : Robert Bickel
ISBN : 9781609181062
Genre : Psychology
File Size : 27. 13 MB
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This book provides a uniquely accessible introduction to multilevel modeling, a powerful tool for analyzing relationships between an individual-level dependent variable, such as student reading achievement, and individual-level and contextual explanatory factors, such as gender and neighborhood quality. Helping readers build on the statistical techniques they already know, Robert Bickel emphasizes the parallels with more familiar regression models, shows how to do multilevel modeling using SPSS, and demonstrates how to interpret the results. He discusses the strengths and limitations of multilevel analysis and explains specific circumstances in which it offers (or does not offer) methodological advantages over more traditional techniques. Over 300 dataset examples from research on educational achievement, income attainment, voting behavior, and other timely issues are presented in numbered procedural steps.

Longitudinal And Panel Data

Author : Edward W. Frees
ISBN : 0521535387
Genre : Business & Economics
File Size : 83. 30 MB
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An introduction to foundations and applications for quantitatively oriented graduate social-science students and individual researchers.

Multilevel Modeling In Plain Language

Author : Karen Robson
ISBN : 9781473934313
Genre : Social Science
File Size : 62. 38 MB
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Have 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? Help 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. This book is the perfect answer for anyone who needs a clear, accessible introduction to multilevel modeling.

Applied Regression Analysis And Generalized Linear Models

Author : John Fox
ISBN : 9781483310886
Genre : Social Science
File Size : 80. 55 MB
Format : PDF, Kindle
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Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book.

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