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Categorical Data Analysis and Multilevel Modeling Using R

Categorical Data Analysis and Multilevel Modeling Using R provides a practical guide to regression techniques for analyzing binary, ordinal;

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Multilevel Modeling of Categorical Outcomes Using IBM SPSS

learn how to develop, estimate, and interpret multilevel models with categorical outcomes. The authors walk readers through data management;

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Multilevel Modeling of Categorical Outcomes Using IBM SPSS

learn how to develop, estimate, and interpret multilevel models with categorical outcomes. The authors walk readers through data management;

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Applied Ordinal Logistic Regression Using Stata: From Single-Level to Multilevel Modeling

Provides a unified framework for both single-level and multilevel modeling of ordinal categorical data;

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Multilevel Modeling Using R

models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the;

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Multilevel Modeling Using R

models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the;

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Multilevel Modeling Techniques and Applications in Institutional Research

themselves to multilevel modeling techniques. As data-driven decision making becomes more critical to colleges and universities, multilevel modeling;

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Modern Methods for Business Research

analysis, dynamic factor analysis, partial least squares and structural equation modeling, multilevel data analysis, modeling of longitudinal data;

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Modern Methods for Business Research

analysis, dynamic factor analysis, partial least squares and structural equation modeling, multilevel data analysis, modeling of longitudinal data;

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Multilevel Modeling

Multilevel Modeling is a concise, practical guide to building models for multilevel and longitudinal data. Author Douglas A. Luke begins by;

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Multilevel Modeling

Multilevel Modeling: Applications in STATA (R), IBM (R) SPSS (R), SAS (R), R & HLM (TM) provides a gentle, hands-on illustration of the;

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Bayesian Statistics for the Social Sciences

. Part III extends Bayesian statistics to multilevel modeling and modeling for continuous and categorical latent variables. Kaplan closes with a;

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Categorical Data Analysis Using the SAS System, Second Edition

discusses various modeling strategies available for describing the nature of the association between a categorical outcome measure and a set;

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Structural Equation Modeling

graphical displays of data and analysis results. Intended as both a teaching resource and a reference guide, and written in non-mathematical;

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Statistical Rethinking

into the main text Illustrates concepts through worked data analysis examples Emphasizes understanding assumptions and how;

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Exploratory Multivariate Analysis by Example Using R

Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four;

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Exploratory Multivariate Analysis by Example Using R

Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four;

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An Introduction to Multilevel Modeling Techniques

, behavioural, health, and social sciences disciplines. Multilevel data analysis exploits data structures that cannot be adequately investigated using;

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An Introduction to Multilevel Modeling Techniques

, behavioural, health, and social sciences disciplines. Multilevel data analysis exploits data structures that cannot be adequately investigated using;

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Discrete Data Analysis with R

An Applied Treatment of Modern Graphical Methods for Analyzing Categorical Data Discrete Data Analysis with R: Visualization and;

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Analysis of Categorical Data with R

Learn How to Properly Analyze Categorical DataAnalysis of Categorical Data with R presents a modern account of categorical data analysis;

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Statistical Methods for Categorical Data Analysis

This book provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social;

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Multilevel Modeling of Social Problems

of multilevel data structures enables researchers to combine contextual and longitudinal analyses appropriately. But researchers working on social;

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Multilevel Modeling of Social Problems

of multilevel data structures enables researchers to combine contextual and longitudinal analyses appropriately. But researchers working on social;

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Handbook of Advanced Multilevel Analysis

-classified models, and dyadic data analysis. Intended for methodologists, statisticians, and researchers in a variety of fields including;

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Introduction to Modern Modelling Methods

) * Longitudinal Modeling using multilevel and SEM techniques * Combining organizational and longitudinal models Part of The SAGE;

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Regression Models for Categorical, Count, and Related Variables

Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or;

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