Home / Research Support / Statistics & Methods Core / Data Lab / Classic Non-Technical Statistical and Research Methods Texts

R.I.S.E. Contact

General email
CONHIresearch@asu.edu

David W. Coon, PhD
David.W.Coon@asu.edu
602-496-0763
Associate Dean, R.I.S.E and Professor
HLTHS 216

Diane Kapp
Diane.Kapp@asu.edu
602-496-1735
Administrative Specialist
HLTHS 221

Deb Fisher
Deb.Fisher@asu.edu
602-496-0931
Asst Director, Research Advancement
HLTHS 224

Lisa Cole
Lisa.Cole@asu.edu
602-496-0196
Research Advancement Administrator, Pre-Award focus
HLTHS 223

Pam Winfrey
Pamela.Winfrey@asu.edu
602-496-0688
Research Advancement Administrator, Post-Award focus
HLTHS 225

Jeffrey Walker
Jeffrey.J.Walker@asu.edu
602-496-1690
Business Operations Specialists, Sr.

Keenan Pituch
Keenan.Pituch@asu.edu
602-496-2480
Research Professor
HLTHS 230

Michael W. Todd, PhD
agmwt@mainex1.asu.edu
602-496-0917
Associate Research Professor
HLTHS 220

SeungYong Han
shan32@asu.edu
602-496-1960
Associate Research Professor / Data Lab Manager
HLTHS 228

Shaun O'Brien
shaunobrien@asu.edu
602-496-0845
Editor, Research & Special Projects
HLTHS 225


Classic Non-Technical Statistical and Research Methods Texts

Introductory statistics

  • Andy Field: Discovering Statistics Using IBM SPSS Statistics, 4th Edition.
  • Robert R. Pagano: Understanding Statistics in the Behavioral Sciences, 10th Edition.

Regression

  • Jacob Cohen and Patricia Cohen: Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences, 3rd Edition.
  • Michael Kutner, Christopher Nachtsheim, John Neter, William Li: Applied Linear Statistical Models, 5th Edition.
  • William Mendenhall and Terry T Sincich: A Second Course in Statistics: Regression Analysis, 7th Edition.

Design of experiments

  • Geoffrey Keppel and Thomas D. Wickens: Design and Analysis: A Researcher's Handbook, 4th Edition.
  • Roger E. Kirk: Experimental Design: Procedures for the Behavioral Sciences, 4th Edition.

Categorical data analysis

  • Alan Agresti : An Introduction to Categorical Data Analysis, 2nd Edition.
  • Razia Azen¬† and Cindy M. Walker: Categorical Data Analysis for the Behavioral and Social Sciences.

Multivariate statistics

  • Barbara G. Tabachnick and Linda S. Fidell: Using Multivariate Statistics, 6th Edition.
  • James P. Stevens: Applied Multivariate Statistics for the Social Sciences, 5th Edition.
  • Joseph F. Hair Jr, William C. Black, Barry J. Babin, Rolph E. Anderson: Multivariate Data Analysis, 7th Edition.
  • Lawrence S. Meyers, Glenn C. Gamst, Anthony J. Guarino: Applied Multivariate Research: Design and Interpretation, 2nd Edition.
  • Sam Kash Kachigan: Multivariate Statistical Analysis: A Conceptual Introduction, 2nd Edition.

Bayesian statistics

  • David Kaplan: Bayesian Statistics for the Social Sciences.
  • Jeff Gill: Bayesian Methods: A Social and Behavioral Sciences Approach, 3rd Edition.
  • John Kruschke: Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan.
  • Roy Levy and Robert J. Mislevy: Bayesian Psychometric Modeling.

Structural Equation Modeling

  • Barbara M. Byrne: Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming, 3rd Edition.
  • Norm O'Rourke and Larry Hatcher: A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling, 2nd Edition.
  • Randall E. Schumacker and Richard G. Lomax: A Beginner's Guide to Structural Equation Modeling, 4th Edition.
  • Rex B. Kline: Principles and Practice of Structural Equation Modeling, 4th Edition.
  • Rick H. Hoyle: Handbook of Structural Equation Modeling.
  • Todd D. Little and Noel A. Card: Longitudinal Structural Equation Modeling.

Multilevel modeling

  • Andrew Gelman and Jennifer Hill: Data Analysis Using Regression and Multilevel/Hierarchical Models.
  • Joop J. Hox, Mirjam Moerbeek, and Rens van de Schoot: Multilevel Analysis: Techniques and Applications, 2nd Edition.
  • Ronald H. Heck and Scott L. Thomas: Multilevel and Longitudinal Modeling with IBM SPSS, 2nd Edition.
  • Ronald H Heck, Scott Thomas, and Lynn Tabata: Multilevel Modeling of Categorical Outcomes Using IBM SPSS.
  • Stephen W. Raudenbush¬† and Anthony S. Bryk: Hierarchical Linear Models: Applications and Data Analysis Methods, 2nd Edition.

Testing and assessment

  • R. J. de Ayala: The Theory and Practice of Item Response Theory.
  • Ronald K. Hambleton: Fundamentals of Item Response Theory.

Statistics programming

  • Lora D. Delwiche and Susan J. Slaughter: The Little SAS Book: A Primer, 5th Edition.
  • Paul Teetor : R Cookbook.

Last revised by Hongwei Yang on Thursday, March 2, 2017 - 1:02pm