Multilevel and Longitudinal Modeling with IBM SPSS, Third Edition, demonstrates how to use the multilevel and longitudinal modeling techniques available in IBM SPSS Versions 25-27. Annotated screenshots with all relevant output provide readers with a step-by-step understanding of each technique as they are shown how to navigate the program. Throughout, diagnostic tools, data management issues, and related graphics are introduced. SPSS commands show the flow of the menu structure a...

Multilevel 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 explore...

Providing a comprehensive review of pressing issues roiling American college campuses today, this book is a valuable resource for students and scholars alike.People often refer to America's colleges and universities as "Ivory Towers," a term that implies that campuses are innocent places of study largely insulated from wider societal concerns. In actuality, our nation's universities are hotbeds of controversy. Some of these sources of heated debate relate directly ...

This is the first workbook that introduces the multilevel approach to modeling with categorical outcomes using IBM SPSS Version 20. Readers learn how to develop, estimate, and interpret multilevel models with categorical outcomes. The authors walk readers through data management, diagnostic tools, model conceptualization, and model specification issues related to single-level and multilevel models with categorical outcomes. Screen shots clearly demonstrate techniques and navigation of the ...

Marketing researchers, companies and business schools need to be able to use statistical procedures correctly and accurately interpret the outputs, yet generally these people are scared off by the statistics behind the different analyses procedures, thus they often rely on external sources to come up with profound answers to the proposed research questions. In an accessible and step by step approach, the authors show readers which procedures to use in which particular situation and how to ...

This book presents the basic procedures for utilizing SAS Enterprise Guide to analyze statistical data. SAS Enterprise Guide is a graphical user interface (point and click) to the main SAS application. Each chapter contains a brief conceptual overview and then guides the reader through concrete step-by-step examples to complete the analyses. The eleven sections of the book cover a wide range of statistical procedures including descriptive statistics, correlation and simple regression, t te...

This bestselling text provides a practical guide to structural equation modeling (SEM) using the Amos Graphical approach. Using clear, everyday language, the text is ideal for those with little to no exposure to either SEM or Amos. The author reviews SEM applications based on actual data taken from her own research. Each chapter "walks" readers through the steps involved (specification, estimation, evaluation, and post hoc modification) in testing a variety of SEM models. Accompanying each...

This book provides a refreshing and user-friendly guide to quantitative data analysis in education for students and researchers. It assumes absolutely no prior knowledge of quantitative methods or statistics. Beginning with the very basics, it provides the reader with the knowledge and skills necessary to be able to undertake routine quantitative data analysis to a level expected of published research.Rather than focusing on teaching statistics through mathematical formulae, the bo...

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...

Understanding Statistics in the Behavioral Sciences is designed to help readers understand research reports, analyze data, and familiarize themselves with the conceptual underpinnings of statistical analyses used in behavioral science literature. The authors review statistics in a way that is intended to reduce anxiety for students who feel intimidated by statistics. Conceptual underpinnings and practical applications are stressed, whereas algebraic derivations and complex formula...

This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help readers quickly understand LVMs and their analysis in R. The author reviews the reasoning behind the syntax selected and provides examples that demonstrate how to analyze data for a variety of LVMs. Featuring examples applicable to psychology, education, business, and ot...

This fully updated edition of Statistics for Research explains statistical concepts in a straight-forward and accessible way using practical examples from a variety of disciplines. If you′re looking for an easy-to-read, comprehensive introduction to statistics with a guide to SPSS, this is the book for you!The new edition features:- Clear explanations of all the main techniques of statistical analysis- A brand new student-friendly, easy-to-navigate design- E...