000			03142nam a22002537a 4500
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008			251018b |||||||| |||| 00| 0 eng d
020			_a9780367182441
082			_a001.422 _bHEC
100			_aHeck, Ronald _925707
245			_aAn introduction to multilevel modeling techniques: _bMLM and SEM approaches
250			_a4th
260			_aNew York _bRoutledge _c2020
300			_axv, 388 p.
365			_aGBP _b57.99
490			_aQuantitative Methodology Series
500			_aTable of contents: Preface 1. Introduction 2. Getting Started with Multilevel Analysis 3. Multilevel Regression Models 4. Extending the Two-Level Regression Model 5. Methods for Examining Individual and Organizational Change 6. Multilevel Models with Categorical Variables 7. Multilevel Structural Equation Variables 8. Multilevel Latent Growth and Mixture Models 9. Data Consideration in Examining Multilevel Models [https://www.routledge.com/An-Introduction-to-Multilevel-Modeling-Techniques-MLM-and-SEM-Approaches/Heck-Thomas/p/book/9780367182441]
520			_aMultilevel modelling is a data analysis method that is frequently used to investigate hierarchal data structures in educational, behavioural, health, and social sciences disciplines. Multilevel data analysis exploits data structures that cannot be adequately investigated using single-level analytic methods such as multiple regression, path analysis, and structural modelling. This text offers a comprehensive treatment of multilevel models for univariate and multivariate outcomes. It explores their similarities and differences and demonstrates why one model may be more appropriate than another, given the research objectives. New to this edition: An expanded focus on the nature of different types of multilevel data structures (e.g., cross-sectional, longitudinal, cross-classified, etc.) for addressing specific research goals; Varied modelling methods for examining longitudinal data including random-effect and fixed-effect approaches; Expanded coverage illustrating different model-building sequences and how to use results to identify possible model improvements; An expanded set of applied examples used throughout the text; Use of four different software packages (i.e., Mplus, R, SPSS, Stata), with selected examples of model-building input files included in the chapter appendices and a more complete set of files available online. This is an ideal text for graduate courses on multilevel, longitudinal, latent variable modelling, multivariate statistics, or advanced quantitative techniques taught in psychology, business, education, health, and sociology. Recommended prerequisites are introductory univariate and multivariate statistics. (https://www.routledge.com/An-Introduction-to-Multilevel-Modeling-Techniques-MLM-and-SEM-Approaches/Heck-Thomas/p/book/9780367182441)
650			_aMultivariate statistics _916027
650			_aQuantitative techniques--Business _925708
650			_aQuantitative technique--Mathematics _925709
700			_aThomas, Scott L. _925710
942			_cBK _2ddc
999			_c10205 _d10205