Spurious Predictors in Random Coefficient Modeling PDF Download
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Author: Michael Thomas Braun
Publisher:
ISBN:
Category : Longitudinal method
Languages : en
Pages : 184
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Book Description
Author: Michael Thomas Braun
Publisher:
ISBN:
Category : Longitudinal method
Languages : en
Pages : 184
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Book Description
Author: Jose M. Cortina
Publisher: Routledge
ISBN: 1135068453
Category : Education
Languages : en
Pages : 525
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Book Description
The goal of the chapters in this SIOP Organizational Frontiers Series volume is to challenge researchers to break away from the rote application of traditional methodologies and to capitalize upon the wealth of data collection and analytic strategies available to them. In that spirit, many of the chapters in this book deal with methodologies that encourage organizational scientists to re-conceptualize phenomena of interest (e.g., experience sampling, catastrophe modeling), employ novel data collection strategies (e.g., data mining, Petri nets), and/or apply sophisticated analytic techniques (e.g., latent class analysis). The editors believe that these chapters provide compelling solutions for the complex problems faced by organizational researchers.
Author: G. David Garson
Publisher: SAGE
ISBN: 1412998859
Category : Mathematics
Languages : en
Pages : 393
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Book Description
This book provides a brief, easy-to-read guide to implementing hierarchical linear modeling using three leading software platforms, followed by a set of original how-to applications articles following a standardard instructional format. The "guide" portion consists of five chapters by the editor, providing an overview of HLM, discussion of methodological assumptions, and parallel worked model examples in SPSS, SAS, and HLM software. The "applications" portion consists of ten contributions in which authors provide step by step presentations of how HLM is implemented and reported for introductory to intermediate applications.
Author: Joop J. Hox
Publisher: Routledge
ISBN: 1136975357
Category : Education
Languages : en
Pages : 393
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Book Description
This practical introduction helps readers apply multilevel techniques to their research. Noted as an accessible introduction, the book also includes advanced extensions, making it useful as both an introduction and as a reference to students, researchers, and methodologists. Basic models and examples are discussed in non-technical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines. For example, readers will find data sets on stress in hospitals, GPA scores, survey responses, street safety, epilepsy, divorce, and sociometric scores, to name a few. The data sets are available on the website in SPSS, HLM, MLwiN, LISREL and/or Mplus files. Readers are introduced to both the multilevel regression model and multilevel structural models. Highlights of the second edition include: Two new chapters—one on multilevel models for ordinal and count data (Ch. 7) and another on multilevel survival analysis (Ch. 8). Thoroughly updated chapters on multilevel structural equation modeling that reflect the enormous technical progress of the last few years. The addition of some simpler examples to help the novice, whilst the more complex examples that combine more than one problem have been retained. A new section on multivariate meta-analysis (Ch. 11). Expanded discussions of covariance structures across time and analyzing longitudinal data where no trend is expected. Expanded chapter on the logistic model for dichotomous data and proportions with new estimation methods. An updated website at http://www.joophox.net/ with data sets for all the text examples and up-to-date screen shots and PowerPoint slides for instructors. Ideal for introductory courses on multilevel modeling and/or ones that introduce this topic in some detail taught in a variety of disciplines including: psychology, education, sociology, the health sciences, and business. The advanced extensions also make this a favorite resource for researchers and methodologists in these disciplines. A basic understanding of ANOVA and multiple regression is assumed. The section on multilevel structural equation models assumes a basic understanding of SEM.
Author: Martin Moryson
Publisher: Springer Science & Business Media
ISBN: 3642997996
Category : Mathematics
Languages : en
Pages : 326
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Book Description
Regression and state space models with time varying coefficients are treated in a thorough manner. State space models are introduced as a means to model time varying regression coefficients. The Kalman filter and smoother recursions are explained in an easy to understand fashion. The main part of the book deals with testing the null hypothesis of constant regression coefficients against the alternative that they follow a random walk. Different exact and large sample tests are presented and extensively compared based on Monte Carlo studies, so that the reader is guided in the question which test to choose in a particular situation. Moreover, different new tests are proposed which are suitable in situations with autocorrelated or heteroskedastic errors. Additionally, methods are developed to test for the constancy of regression coefficients in situations where one knows already that some coefficients follow a random walk, thereby one is enabled to find out which of the coefficients varies over time.
Author: John W. Henderson
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 126
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Book Description
Author: Jason Beckfield
Publisher: Oxford University Press
ISBN: 019049428X
Category : Social Science
Languages : en
Pages : 224
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Book Description
The Euro-crisis of 2009-2012 vividly demonstrated that European Union policies matter for the distribution of resources within and between European nation-states. Throughout the crisis, distributive conflicts between the EU's winners and losers worsened, and are still reverberating in European politics today. In Unequal Europe, Jason Beckfield demonstrates that there is a direct connection between European integration and the increase in European income inequality over the past four decades. He places the recent crisis into a broader sociological, political, and economic perspective by analyzing how European integration has reshaped the distribution of income across the households of Europe. Using individual-and household-level income survey data, combined with macro-level data on social policies, and case studies of welfare reforms in EU and non-EU states, Beckfield shows how European integration has re-stratified Europe by simultaneously drawing national economies closer together and increasing inequality among households. Explaining how, where, and why income inequality has changed in the EU, Unequal Europe answers the question: who wins and who loses from European integration?
Author: Constantin Colonescu
Publisher: Lulu.com
ISBN: 1387473611
Category : Business & Economics
Languages : en
Pages : 278
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Book Description
This is a beginner's guide to applied econometrics using the free statistics software R. It provides and explains R solutions to most of the examples in 'Principles of Econometrics' by Hill, Griffiths, and Lim, fourth edition. 'Using R for Principles of Econometrics' requires no previous knowledge in econometrics or R programming, but elementary notions of statistics are helpful.
Author: Dirk Speelman
Publisher: Springer
ISBN: 3319698303
Category : Social Science
Languages : en
Pages : 149
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Book Description
When data consist of grouped observations or clusters, and there is a risk that measurements within the same group are not independent, group-specific random effects can be added to a regression model in order to account for such within-group associations. Regression models that contain such group-specific random effects are called mixed-effects regression models, or simply mixed models. Mixed models are a versatile tool that can handle both balanced and unbalanced datasets and that can also be applied when several layers of grouping are present in the data; these layers can either be nested or crossed. In linguistics, as in many other fields, the use of mixed models has gained ground rapidly over the last decade. This methodological evolution enables us to build more sophisticated and arguably more realistic models, but, due to its technical complexity, also introduces new challenges. This volume brings together a number of promising new evolutions in the use of mixed models in linguistics, but also addresses a number of common complications, misunderstandings, and pitfalls. Topics that are covered include the use of huge datasets, dealing with non-linear relations, issues of cross-validation, and issues of model selection and complex random structures. The volume features examples from various subfields in linguistics. The book also provides R code for a wide range of analyses.
Author: Jeremy Miles
Publisher: SAGE
ISBN: 9780761962304
Category : Mathematics
Languages : en
Pages : 266
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Book Description
Takes a look at applying regression analysis in the behavioural sciences by introducing the reader to regression analysis through a simple model-building approach.
