• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
The Analysis Factor

The Analysis Factor

Statistical Consulting, Resources, and Statistics Workshops for Researchers

  • Home
  • About
    • Our Programs
    • Our Team
    • Our Core Values
    • Our Privacy Policy
    • Employment
    • Guest Instructors
  • Membership
    • Statistically Speaking Membership Program
    • Login
  • Workshops
    • Online Workshops
    • Login
  • Consulting
    • Statistical Consulting Services
    • Login
  • Free Webinars
  • Contact
  • Login

Mixed and Multilevel Models

Online Workshops

  • Analyzing Repeated Measures Data: ANOVA and Mixed Model Approaches
  • Introduction to Generalized Linear Mixed Models

The Craft of Statistical Analysis Webinars The Craft of Statistical Analysis

  • Random Intercept and Random Slope Models
  • Fixed and Random Factors in Mixed Models

Statistically Speaking Trainings

  • Crossed and Nested Factors
  • Latent Growth Curve Models
  • Matrix Algebra for Data Analysts: A Primer
  • Power Analysis and Sample Size Determination Using Simulation

Articles at The Analysis Factor

  • The Unstructured Covariance Matrix: When It Does and Doesn’t Work
  • Covariance Matrices, Covariance Structures, and Bears, Oh My!
  • Approaches to Repeated Measures Data: Repeated Measures ANOVA, Marginal, and Mixed Models
  • Sample Size Estimates for Multilevel Randomized Trials
  • Five Extensions of the General Linear Model
  • The Repeated and Random Statements in Mixed Models for Repeated Measures
  • How Simple Should a Model Be? The Case of Insignificant Controls, Interactions, and Covariance Structures
  • The Difference Between Clustered, Longitudinal, and Repeated Measures Data
  • When the Hessian Matrix goes Wacky
  • Five Advantages of Running Repeated Measures ANOVA as a Mixed Model
  • Concepts in Linear Regression you need to know before learning Multilevel Models
  • Multilevel Models with Crossed Random Effects
  • Confusing Statistical Terms #3: Levels of a Factor in Multilevel Models Measured at a Nominal Level
  • Assessing the Fit of Regression Models
  • Mixed Up Mixed Models
  • Specifying Fixed and Random Factors in Mixed Models

Books

  • SAS for Mixed Models, Second Edition by Ramon Littell, George Miliken, Walter Stroup, Russell Wolfinger, & Oliver Schabenberger

    This is a pretty technical book, and is not for the statistically feeble. But if you’re doing mixed models, you’re not statistically feeble. That said, if you are doing Mixed Modeling in SAS, it’s a must-have book. Back in the Cornell Statistical Consulting office, we actually wore out the book.

  • Quantitative Methods in Population Health: Extensions of Ordinary Regression by Mari Palta
  • Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence by Judith D. Singer & John B. Willett
  • Multilevel Analysis for Applied Research: It’s Just Regression! (Methodology In The Social Sciences) by Robert Bickel PhD
  • Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling by Professor Tom A.B. Snijders and Professor Roel Bosker
  • Linear Mixed Models: A Practical Guide Using Statistical Software by Brady West, Kathleen B. Welch and Andrzej T Galecki

Journal Articles

  • Arnold, Carolyn L. (1992) An Introduction to Hierarchical Linear Models. Measurement and Evaluation in Counseling and Development, 25, 58-90.
  • Singer, Judith D. (1998) Using SAS PROC MIXED to Fit Multilevel Models, Hierarchial Models, and Individual Growth Models. Journal of Educational and Behavioral Statistics, 24, 323-355.
  • Plewis, Ian. (1998) Multilevel Models. Social Research Update, 23.
  • Harner, Robert & Simpson, P.M. (2000). Mixed-Up Mixed Models: Things That Look Like They Should Work But Don’t, and Things That Look Like They Shouldn’t Work But Do. Presented at SUGI.

Web Sources

http://www.lesahoffman.com/Research/MLM.html:

Dr. Lesa Hoffman, of the University of Nebraska, has put on her website her entire lecture slides and podcasts for all her classes and workshops, including:

  • Advanced Multilevel Models
  • Latent Trait Measurement Models
  • Multilevel Models for Longitudinal Data

It includes MPlus, SAS, and SPSS examples.

Reader Interactions

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Primary Sidebar

This Month’s Statistically Speaking Live Training

  • February Member Training: Choosing the Best Statistical Analysis

Upcoming Workshops

  • Logistic Regression for Binary, Ordinal, and Multinomial Outcomes (May 2021)
  • Introduction to Generalized Linear Mixed Models (May 2021)

Read Our Book



Data Analysis with SPSS
(4th Edition)

by Stephen Sweet and
Karen Grace-Martin

Statistical Resources by Topic

  • Fundamental Statistics
  • Effect Size Statistics, Power, and Sample Size Calculations
  • Analysis of Variance and Covariance
  • Linear Regression
  • Complex Surveys & Sampling
  • Count Regression Models
  • Logistic Regression
  • Missing Data
  • Mixed and Multilevel Models
  • Principal Component Analysis and Factor Analysis
  • Structural Equation Modeling
  • Survival Analysis and Event History Analysis
  • Data Analysis Practice and Skills
  • R
  • SPSS
  • Stata

Copyright © 2008–2021 The Analysis Factor, LLC. All rights reserved.
877-272-8096   Contact Us

The Analysis Factor uses cookies to ensure that we give you the best experience of our website. If you continue we assume that you consent to receive cookies on all websites from The Analysis Factor.
Continue Privacy Policy
Privacy & Cookies Policy

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary
Always Enabled

Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.

Non-necessary

Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.

SAVE & ACCEPT