This new text provides the most current coverage of measurement and psychometrics in a single volume. Authors W. Holmes Finch and Brian F. French first review the basics of psychometrics and measurement, before moving on to more complex topics such as equating and scaling, item response theory, standard setting, and computer adaptive testing. Also included are discussions of cutting-edge topics utilized by practitioners in the field, such as automated test development, game-based assessment, and automated test scoring. This book is ideal for use as a primary text for graduate-level psychometrics/measurement courses, as well as for researchers in need of a broad resource for understanding test theory. Features: "How it Works" and "Psychometrics in the Real World" boxes break down important concepts through worked examples, and show how theory can be applied to practice. End-of-chapter exercises allow students to test their comprehension of the material, while suggested readings and website links provide resources for further investigation. A collection of free online resources include the full output from R, SPSS, and Excel for each of the analyses conducted in the book, as well as additional exercises, sample homework assignments, answer keys, and PowerPoint lecture slides.

This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results. Each chapter features a detailed example including the analysis of the data using R, the relevant theory, the assumptions underlying the model, and other statistical details to help readers better understand the models and interpret the results. Every R command necessary for conducting the analyses is described along with the resulting output which provides readers with a template to follow when they apply the methods to their own data. The basic information pertinent to each model, the newest developments in these areas, and the relevant R code to use them are reviewed. Each chapter also features an introduction, summary, and suggested readings. A glossary of the text's boldfaced key terms and key R commands serve as helpful resources. The book is accompanied by a website with exercises, an answer key, and the in-text example data sets. Latent Variable Modeling with R: -Provides some examples that use messy data providing a more realistic situation readers will encounter with their own data. -Reviews a wide range of LVMs including factor analysis, structural equation modeling, item response theory, and mixture models and advanced topics such as fitting nonlinear structural equation models, nonparametric item response theory models, and mixture regression models. -Demonstrates how data simulation can help researchers better understand statistical methods and assist in selecting the necessary sample size prior to collecting data. -www.routledge.com/9780415832458 provides exercises that apply the models along with annotated R output answer keys and the data that corresponds to the in-text examples so readers can replicate the results and check their work. The book opens with basic instructions in how to use R to read data, download functions, and conduct basic analyses. From there, each chapter is dedicated to a different latent variable model including exploratory and confirmatory factor analysis (CFA), structural equation modeling (SEM), multiple groups CFA/SEM, least squares estimation, growth curve models, mixture models, item response theory (both dichotomous and polytomous items), differential item functioning (DIF), and correspondance analysis. The book concludes with a discussion of how data simulation can be used to better understand the workings of a statistical method and assist researchers in deciding on the necessary sample size prior to collecting data. A mixture of independently developed R code along with available libraries for simulating latent models in R are provided so readers can use these simulations to analyze data using the methods introduced in the previous chapters. Intended for use in graduate or advanced undergraduate courses in latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, and social and health sciences, researchers in these fields also appreciate this book's practical approach. The book provides sufficient conceptual background information to serve as a standalone text. Familiarity with basic statistical concepts is assumed but basic knowledge of R is not.

Following the publication of his revised translations in "The Apostolic Fathers in English," 3rd ed., Michael Holmes, a leading expert on these texts, offers a thoroughly revised and redesigned bilingual edition, featuring Greek (or Latin) and English on facing pages. Introductions and bibliographies are generous and up to date. In the textual apparatus, existing notes have been revised and expanded, and well over 200 new notes have been added. This handsome and handy one-volume, thin-paper edition will be an essential resource for students and scholars and a joy to book lovers.

This Symposium was the fourth in a series which began in Milan, Italy, in 1960. Each meeting has introduced or developed some new concepts in the areas of lipid metabolism and drugs. The meetings have served as a springboard for new ideas which have, between meetings, become accepted and exploited. This meeting has been no exception. Principal among the many new concepts discussed were lipoprotein synthesis and metabolism, apoprotein structure and function, whole body metabolism of cholesterol, and aspects of myocardial and aortic metabolism. The Symposium also included a summary of current thought on management of hyperlipemias and atherosclerosis. Data on more than 30 drugs were introduced and discussed. We have every expectation that the next Symposium will include material which is now only in the formative stage. The Organizing Committee would like to acknowledge the invaluable assistance of Miss Mary Constant, Mr. Ralph H. Hollerorth, Mrs. Carolyn P. Hyatt and Miss Jane T. Kolimaga, whose efforts contributed significantly (p < .001) to the success of this Symposium.

With over 9 million Americans practicing Pilates, the popular core exercise system is taking the world by storm. While many find the system helps to strengthen the core, improve posture, and recover from or prevent injuries and pain, Pilates has been clouded in controversy since the beginning. Its origin story is one of greed, ego, celebrities, and lies, with heated legal controversy that threatened the industry. In The Pilates Effect, Stacey Redfield and Sarah Holmes reveal the hidden history of Pilates. From humble beginnings, Joseph Pilates founded the groundbreaking regimen in New York City and worked closely with his partner Clara to rehabilitate and renew dancers who had been injured or were aging. Although Joseph's core strengthening regime was touted as "fifty years ahead of [its] time," finance and health issues plagued Joe and Clara's business. A small and devoted group of followers, including Carola Trier, would fight to spread the practice that they felt gave them a second chance at life and rehabilitated their bodies and souls. A fascinating and inspiring story of fitness in America, The Pilates Effect showcases the people and events that formed an iconic industry. Redfield and Holmes offer inspiration and practical advice for how Pilates can offer change for everyday people regardless of gender, ethnicity, or background.

This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results. Each chapter features a detailed example including the analysis of the data using R, the relevant theory, the assumptions underlying the model, and other statistical details to help readers better understand the models and interpret the results. Every R command necessary for conducting the analyses is described along with the resulting output which provides readers with a template to follow when they apply the methods to their own data. The basic information pertinent to each model, the newest developments in these areas, and the relevant R code to use them are reviewed. Each chapter also features an introduction, summary, and suggested readings. A glossary of the text's boldfaced key terms and key R commands serve as helpful resources. The book is accompanied by a website with exercises, an answer key, and the in-text example data sets. Latent Variable Modeling with R: -Provides some examples that use messy data providing a more realistic situation readers will encounter with their own data. -Reviews a wide range of LVMs including factor analysis, structural equation modeling, item response theory, and mixture models and advanced topics such as fitting nonlinear structural equation models, nonparametric item response theory models, and mixture regression models. -Demonstrates how data simulation can help researchers better understand statistical methods and assist in selecting the necessary sample size prior to collecting data. -www.routledge.com/9780415832458 provides exercises that apply the models along with annotated R output answer keys and the data that corresponds to the in-text examples so readers can replicate the results and check their work. The book opens with basic instructions in how to use R to read data, download functions, and conduct basic analyses. From there, each chapter is dedicated to a different latent variable model including exploratory and confirmatory factor analysis (CFA), structural equation modeling (SEM), multiple groups CFA/SEM, least squares estimation, growth curve models, mixture models, item response theory (both dichotomous and polytomous items), differential item functioning (DIF), and correspondance analysis. The book concludes with a discussion of how data simulation can be used to better understand the workings of a statistical method and assist researchers in deciding on the necessary sample size prior to collecting data. A mixture of independently developed R code along with available libraries for simulating latent models in R are provided so readers can use these simulations to analyze data using the methods introduced in the previous chapters. Intended for use in graduate or advanced undergraduate courses in latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, and social and health sciences, researchers in these fields also appreciate this book's practical approach. The book provides sufficient conceptual background information to serve as a standalone text. Familiarity with basic statistical concepts is assumed but basic knowledge of R is not.

The NIV Application Commentary helps you communicate and apply biblical text effectively in today's context. To bring the ancient messages of the Bible into today's world, each passage is treated in three sections: Original Meaning. Concise exegesis to help readers understand the original meaning of the biblical text in its historical, literary, and cultural context. Bridging Contexts. A bridge between the world of the Bible and the world of today, built by discerning what is timeless in the timely pages of the Bible. Contemporary Significance. This section identifies comparable situations to those faced in the Bible and explores relevant application of the biblical messages. The author alerts the readers of problems they may encounter when seeking to apply the passage and helps them think through the issues involved. This unique, award-winning commentary is the ideal resource for today's preachers, teachers, and serious students of the Bible, giving them the tools, ideas, and insights they need to communicate God's Word with the same powerful impact it had when it was first written.

This new text provides the most current coverage of measurement and psychometrics in a single volume. Authors W. Holmes Finch and Brian F. French first review the basics of psychometrics and measurement, before moving on to more complex topics such as equating and scaling, item response theory, standard setting, and computer adaptive testing. Also included are discussions of cutting-edge topics utilized by practitioners in the field, such as automated test development, game-based assessment, and automated test scoring. This book is ideal for use as a primary text for graduate-level psychometrics/measurement courses, as well as for researchers in need of a broad resource for understanding test theory. Features: "How it Works" and "Psychometrics in the Real World" boxes break down important concepts through worked examples, and show how theory can be applied to practice. End-of-chapter exercises allow students to test their comprehension of the material, while suggested readings and website links provide resources for further investigation. A collection of free online resources include the full output from R, SPSS, and Excel for each of the analyses conducted in the book, as well as additional exercises, sample homework assignments, answer keys, and PowerPoint lecture slides.

How did earliest Christians receive and understand the teaching of Jesus and the apostles? These writings, among the earliest used in training new disciples, show a clear, vibrant, practical faith concerned with all aspects of discipleship in daily life-vocation, morality, family life, social justice, the sacraments, prophesy, citizenship, and leadership. For the most part, these writings have remained buried in academia, analyzed by scholars but seldom used for building up the church community. Now, at a time when Christians of every persuasion are seeking clarity by returning to the roots of their faith, these simple, direct teachings shed light on what it means to be a follower of Christ in any time or place. The Didache, an anonymous work composed in the late first century AD, was lost for centuries before being rediscovered in 1873. The Shepherd was written by a former slave named Hermas in the second century AD or possibly even earlier.