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Confirmatory Factor Analysis For Applied Research Second Edition


Author : Timothy A. Brown
language : en
Publisher: Guilford Publications
Release Date : 2015-01-08


PDF Download Confirmatory Factor Analysis For Applied Research Second Edition Books For free written by Timothy A. Brown and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-08 with Psychology categories.


This accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA) for its emphasis on practical and conceptual aspects rather than mathematics or formulas. Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities ...

Abstractband Gmds 2015


Author : Prof. Dr. Bernhard Breil
language : de
Publisher: Pro BUSINESS
Release Date : 2015-09-04


PDF Download Abstractband Gmds 2015 Books For free written by Prof. Dr. Bernhard Breil and has been published by Pro BUSINESS this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-04 with categories.


Die 60. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS) findet vom 6. - 9. September 2015 in Krefeld statt. Aus dem Grußwort von Bernhard Breil/Tagungspräsident 2015: "... die diesjährige Jahrestagung steht unter dem Thema "Fortschritt durch Forschung - Multidisziplinäre Wissenschaft in der GMDS". Fortschritt ist das, was wir Wissenschaftler anstreben. Die GMDS bietet ihre informatischen, biometrischen und epidemiologischen Methoden als "Querschnittsfach" allen medizinischen Teilgebieten in Kooperation an und agiert somit multidisziplinär. Die zahlreichen Beiträge aus den jeweiligen Disziplinen verdeutlichen eindrucksvoll die Bandbreite unserer Fachgesellschaft. Diese Bandbreite findet sich auch an unserer Hochschule im Fachbereich Gesundheitswesen wieder. Projekte wie das Standard-ECG und AKTIN im neu gegründeten Competenc Center eHealth adressieren wichtige Themen, die ihren entsprechenden Stellenwert auf der Jahrestagung haben. Im Projekt Onko-Wiki wird eine webbasierte Wissensplattform als Interpretationshilfe für die Tumordokumentation erstellt, von der vor allem die Medizinischen Dokumentare in den Universitätskliniken profitieren. Im Kompetenzzentrum für Routinedaten im Gesundheitswesen werden biometrische und epidemiologische Methoden angewendet, um beispielsweise krankenhausspezifische Mortalitätsratios unter Berücksichtigung von Komorbidität und anderen Risikofaktoren zu berechnen. Die Ergebnisse dieser Forschung bereichern unsere Studiengänge "eHealth - IT im Gesundheitswesen", Health Care Management und Angewandte Therapiewissenschaften und tragen so zum Leitbild unserer Hochschule bei: Grenzen überwinden ..."

Scale Development


Author : Robert F. DeVellis
language : en
Publisher: SAGE
Release Date : 2003


PDF Download Scale Development Books For free written by Robert F. DeVellis and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Mathematics categories.


'Scale Development' guides the reader toward the identification of the latent variable, the generation of an item pool, the format for measurement & the optimization of the scale length. Using exercises to illustrate the concepts, the text also includes advice about factor analytic strategies.

Strukturgleichungsmodellierung


Author : Rolf Weiber
language : de
Publisher: Springer-Verlag
Release Date : 2014-03-31


PDF Download Strukturgleichungsmodellierung Books For free written by Rolf Weiber and has been published by Springer-Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-31 with Business & Economics categories.


Alle Analysen werden an einem durchgehenden Fallbeispiel konkret und transparent durchgeführt Strukturgleichungsmodelle sind in allen Wissenschaftsdisziplinen von größter Bedeutung, da sie das Standardinstrument zur empirischen Prüfung von Hypothesensystemen darstellen. Dabei stehen oftmals die Beziehungen zwischen hypothetischen Konstrukten (latenten Variablen) im Fokus des Interesses. Das Buch zeichnet den gesamten Prozess der Strukturgleichungsmodellierung von der Konzeptualisierung theoretischer Konstrukte über die Spezifikation von Messmodellen, die Reliabilitäts- und Validitätsprüfung mittels konfirmatorischer Faktorenanalyse bis hin zur Prüfung von kausalen Wirkhypothesen mittels Kovarianzstrukturanalyse sowie PLS nach. Alle Arbeitsschritte werden an einem durchgehenden Fallbeispiel unter Verwendung von SPSS, AMOS und SmartPLS veranschaulicht und jeweils konkrete Anwendungsempfehlungen gegeben. Ebenso werden weiterführende Aspekte wie die Mehrgruppenkausalanalyse, die Spezifikation reflektiver und formativer Messansätze sowie MIMIC-Modelle einsteigergerecht behandelt.

Latent Variable Modeling With R


Author : W. Holmes Finch
language : en
Publisher: Routledge
Release Date : 2015-06-26


PDF Download Latent Variable Modeling With R Books For free written by W. Holmes Finch and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-26 with Psychology categories.


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 Reviewer S Guide To Quantitative Methods In The Social Sciences


Author : Gregory R. Hancock
language : en
Publisher: Routledge
Release Date : 2010-04-26


PDF Download The Reviewer S Guide To Quantitative Methods In The Social Sciences Books For free written by Gregory R. Hancock and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-26 with Education categories.


The Reviewer’s Guide is designed for reviewers of research manuscripts and proposals in the social and behavioral sciences, and beyond. Its uniquely structured chapters address traditional and emerging quantitative methods of data analysis.

The Essence Of Multivariate Thinking


Author : Lisa L. Harlow
language : en
Publisher: Routledge
Release Date : 2014-02-18


PDF Download The Essence Of Multivariate Thinking Books For free written by Lisa L. Harlow and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-18 with Education categories.


By focusing on underlying themes, this book helps readers better understand the connections between multivariate methods. For each method the author highlights: the similarities and differences between the methods, when they are used and the questions they address, the key assumptions and equations, and how to interpret the results. The concepts take center stage while formulas are kept to a minimum. Examples using the same data set give readers continuity so they can more easily apply the concepts. Each method is also accompanied by a worked out example, SPSS and SAS input, and an example of how to write up the results. EQS code is used for the book’s SEM applications. This extensively revised edition features: New SEM chapters including an introduction (ch.10), path analysis (ch.11), confirmatory factor analysis (ch.12), and latent variable modeling (ch.13) the last three with an EQS application. A new chapter on multilevel modeling (ch. 8) that is now used more frequently in the social sciences. More emphasis on significance tests, effect sizes, and confidence intervals to encourage readers to adopt a thorough approach to assessing the magnitude of their findings. A new data set that explores the work environment. More discussion about the basic assumptions and equations for each method for a more accessible approach. New examples that help clarify the distinctions between methods. A new website at https://sites.google.com/site/multivariatesecondedition/ that features the datasets for all of the examples in the book for use in both SPSS and SAS and in EQS for the SEM chapters. The first two chapters review the core themes that run through most multivariate methods. The author shows how understanding multivariate methods is much more achievable when we notice the themes that underlie these statistical techniques. This multiple level approach also provides greater reliability and validity in our research. After providing insight into the core themes, the author illustrates them as they apply to the most popular multivariate methods used in the social, and behavioral sciences. First, two intermediate methods are explored – multiple regression and analysis of covariance. Next the multivariate grouping variable methods of multivariate analysis of variance, discriminant function analysis, and logistic regression are explored. Next the themes are applied to multivariate modeling methods including multilevel modeling, path analysis, confirmatory factor analysis, and latent variable models that include exploratory structural methods of principal component and factor analysis. The book concludes with a summary of the common themes and how they pertain to each method discussed in this book. Intended for advanced undergraduate and/or graduate courses in multivariate statistics taught in psychology, education, human development, business, nursing, and other social and life sciences, researchers also appreciate this book‘s applied approach. Knowledge of basic statistics, research methods, basic algebra, and finite mathematics is recommended.