Data Analysis Using Stata

This book helps public health practitioners and students gain expertise in applications of regression modeling in order to solve problems when data are collected in epidemiological studies. It covers

The authors have led workshops on the subject for the past decade, sponsored each year by the American Psychological Association, and they have written this text in part as a means of encouraging the

Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are

Discovering Structural Equation Modeling Using Stata, Revised Edition is devoted to Stata’s sem command and all it can do. Learn about its capabilities in the context of confirmatory factor analysis,

Meyers (psychology, California State U.-Sacramento), Gamst (psychology, U. of La Verne, California), and Guarino (biostatistics, Massachusetts General Hospital) introduce the commercial statistics pac

In this important new text, Paul Sullivan introduces readers to a qualitative methodology rooted in the analysis of dialogue and subjectivity: the dialogical approach. Sullivan unpacks the theory behi

Too often in biostatistical research and clinical trials, a knowledge gap exists between developed statistical methods and the applications of these methods. Filling this gap, Clinical Trial Data Anal

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 tests, one-way chi square, data transformations, multiple regression, analysis of variance, analysis of covariance, multivariate analysis of variance, factor analysis, and canonical correlation analysis. Designed to be used either as a stand-alone resource or as an accompaniment to a statistics course, the book offers a smooth path to statistical analysis with SAS Enterprise Guide for advanced undergraduate and beginning graduate students, as well as professionals in psychology, education, business, hea

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 tests, one-way chi square, data transformations, multiple regression, analysis of variance, analysis of covariance, multivariate analysis of variance, factor analysis, and canonical correlation analysis. Designed to be used either as a stand-alone resource or as an accompaniment to a statistics course, the book offers a smooth path to statistical analysis with SAS Enterprise Guide for advanced undergraduate and beginning graduate students, as well as professionals in psychology, education, business, hea

Do you want to recognize the most suitable models for analysis of statistical data sets? This book provides a hands-on practical guide to using the most suitable models for analysis of statistical da

Multilevel and Longitudinal Modeling Using Stata, Second Edition discusses regression modeling of clustered or hierarchical data, such as data on students nested in schools, patients in hospitals, or

Useful business analysis requires you to effectively transform data into actionable information. This book helps you use SQL and Excel to extract business information from relational databases and use

This book uses a mathematical approach to deriving the laws of science and technology, based upon the concept of Fisher information. The approach that follows from these ideas is called the principle

The preferred method of data analysis of quantitative experiments is the method of least squares. Often, however, the full power of the method is overlooked, and very few books deal with these techniq

Statistical analysis is ubiquitous in modern medical research. Logistic regression, generalized linear models, random effects models, and Cox's regression all have become commonplace in the medical li

Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival analysis for upper-level or graduate students in statistics, biosta

This book is primarily written for students and researchers dealing with complex ecological problems. Multivariate statistical methods are described, and advice is given on how best to apply these met

This book provides an in-depth roadmap for qualitative research methods and data analysis across disciplines using ATLAS.ti. It encompasses and rationalizes key qualitative research concepts and methods with innovative frameworks to enrich the reader’s understanding of qualitative research methods and data analysis. The book contains multiple real-world projects that assist readers in developing conceptual and theoretical knowledge, as well as gaining insights from fieldwork, visualizing data collection, analysis, and methodological interpretations.This easy to use book provides a pragmatic approach to qualitative methods, proficiency in capturing field observations, user-friendly steps to data analysis starting from transcription, preparation of data, reading and identification of quotations, coding, memoing, commenting, code groups, creating smart codes and groups using set, semantic, and proximity operators resulting in generating numerous insightful thematic reports in avariety of