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Essential #1 best-selling reference for more than 20 years sold in almost every college bookstore in the country. The core statistics course is a critical and difficult class for many and develops a foundation that will support use of statistics in higher level courses in so many subject areas and majors. This six-page laminated guide is filled with more need-to-know facts per page than any book
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Featuring engaging examples from diverse disciplines, this book explains how to use modern approaches to quasi-experimentation to derive credible estimates of treatment effects under the demanding constraints of field settings. Foremost expert Charles S. Reichardt provides an in-depth examination of the design and statistical analysis of pretest–posttest, nonequivalent groups, regression
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Longitudinal Structural Equation Modeling is a comprehensive resource that reviews structural equation modeling (SEM) strategies for longitudinal data to help readers determine which modeling options are available for which hypotheses.This accessibly written book explores a range of models, from basic to sophisticated, including the statistical and conceptual underpinnings that are the building
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Single-Case Methods in Clinical Psychology: A Practical Guide provides a concise and easily-accessible introduction to single-case research. This is a timely response to the increasing awareness of the need to look beyond randomised controlled trials for evidence to support best practice in applied psychology. The book covers the issues of design, the reliability and validity of measurement, and
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ANOVA and Mixed Models: A Short Introduction Using R provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs. Based on knowledge from an introductory course on probability and statistics, the theoretical foundations of the most important models are introduced. The focus is on an intuitive understanding of the theory,
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This second edition of Applied Multivariate Statistical Concepts covers the classic and cutting-edge multivariate techniques used in today’s research.Through clear writing and engaging pedagogy and examples using real data, Hahs-Vaughn walks students through the most used methods to learn why and how to apply each technique. A conceptual approach with a higher than usual text-to-formula ratio ... Read more

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This second edition of Applied Multivariate Statistical Concepts covers the classic and cutting-edge multivariate techniques used in today’s research.Through clear writing and engaging pedagogy and examples using real data, Hahs-Vaughn walks students through the most used methods to learn why and how to apply each technique. A conceptual approach with a higher than usual text-to-formula ratio
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by Marley Watkins ...

This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using Stata.In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of Stata code and recommends evidence-based best practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with ... Read more

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This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using Stata.In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of Stata code and recommends evidence-based best practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with
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Latent Variable Modeling Using R

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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 ... Read more

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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
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The book is a unique blend of quantitative research and statistical analysis using R. Lucidly written, it covers a range of statistical techniques applicable to cross-sectional data in the backdrop of quantitative research and survey research. In addition to the basic concepts, this book also explores advanced multivariate statistics topics like principal components analysis, cluster analysis, ... Read more

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The book is a unique blend of quantitative research and statistical analysis using R. Lucidly written, it covers a range of statistical techniques applicable to cross-sectional data in the backdrop of quantitative research and survey research. In addition to the basic concepts, this book also explores advanced multivariate statistics topics like principal components analysis, cluster analysis,
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Recommended For You

Statistics eBooks

May Contain Lies

Predictably Irrational, Revised and Expanded Edition

Misbehaving

A Guide for the Statistically Perplexed

Dealing with the financial crisis

Narcissist Unmasked

Increasing Awareness of Child and Adolescent Mental Health

Lehrbuch Allgemeine Psychologie

Issue 27

Statistics Alive!

Research Methods and Statistics

Statistical Analysis "In Focus"

Deskriptive Statistik und Wahrscheinlichkeitstheorie

Basic Statistics

Statistics

Quasi-Experimentation

Multilevel and Longitudinal Modeling with IBM SPSS

Longitudinal Structural Equation Modeling

Single Case Methods in Clinical Psychology

ANOVA and Mixed Models

Applied Multivariate Statistical Concepts

A Step-by-Step Guide to Exploratory Factor Analysis with Stata

Latent Variable Modeling Using R

Quantitative Research using R