Karl Jöreskog

New Features in LISREL 9

Karl Jöreskog, Ph.D.

50 Years of SEM in 50 Minutes??

Session 1.1

An Empirical Test of Accountability Policy: A-F School Grades.

Mwarumba Mwavita & Curt Adams.

Longitudinal Models for the Early Development of Hand Preferences.

Richard A. Faldowski, George F. Michel, Iryna Babik, Julie Campbell, & Emily Marcinowski   

Piecewise-Linear Multilevel Models of Sociometric Nominations over the Transition to Middle School.

Richard A. Faldowski, Madelynnn D. Shell, & Heidi Gazelle 

Session 1.2

Bayesian Model Averaging Over Directed Acyclic Graphs with Implications for Prediction in Structural Equation Modeling.

David Kaplan & Chansoon Lee                 

Bayesian Factor Analysis with Variable Selection Techniques.

 Zhaohua Lu, Sy-miin Chow, & Eric Loken 

Session 1.3

Unipolar Item Response Models.

Joseph F. Lucke

Cross Classified Modeling of Dual Local Item Dependence.

Chao Xie & Hong Jiao

Session 1.4

An Empirical Comparison of Multiple Imputation Approaches for Treating Missing Data in Propensity Score Analyses.

 Jessica Montgomery, Eun Sook Kim, Jeffrey D. Kromrey, Rheta E. Lanehart, Patricia Rodriguez de Gil, Yan Wang, & Reginald Lee

Missing Covariates in Causal Inference Matching: Statistical Modeling Using Machine Learning and Evolutionary Search Algorithms.

 Landon Hurley

Session 1.5

Simulating Data for Mixture Model Studies: Considering Measures of Data Overlap

Jeffrey Harring & Junhui Liu         

A Simple Simulation Technique for Non-Normal Data with Pre-Specified Kurtosis and Covariance Matrix.

Ulf Henning Olsson & Njål Foldnes          

Non-normal Data Simulation Using Regular Vines.

 Njål Foldnes & Steffen Grønneberg                      

Session 1.6

Methodological Illustration of Multiple Group Multilevel SEM with LSA Data.

 Agnes Stancel-Piatak

An Evaluation of the Alignment Method for Detecting Measurement Non-invariance in Noncognitive Scales.

 Jessica Kay Flake & Betsy McCoach                    

Exploring Noninvariance in Classroom Behavior Trajectories Using Growth Mixture Modeling.

  Janice Kooken, D. Betsy McCoach, Sandra Chafouleas,  Faith G. Miller, Megan Welsh, T. Chris Riley-Tilman, & & Noel Card

Session 2.1- Symposium

Innovative Developments and Applications in Latent Class Analysis.

  Chair: Jay Magidson

Paper 1: Goodness-of-fit of Multilevel Latent Class Models for Categorical Data.

Erwin Nagelkerke, D. L. Oberski, & Jeroen Vermunt

Paper 2: Micro-macro Multilevel Analysis for Discrete Data.

Margot Sijssens-Bennink, M.A. Croon, & Jeroen Vermunt

Paper 3: Divisive Latent Class Analysis Applied to Social Capital.

Mattis van den Bergh, Verena Schmittmann, & Jeroen Vermunt

Paper 4: Resampling Methods for Assessing Latent Class Model Fit.

Geert van Kolenburg, Joris Mulder, & Jeroen Vermunt

Session 2.2

Assessing Associations and Patterns in Multi-Member Multi-Group Data.

  Thomas Ledermann, Myriam Rudaz, & Alexander Grob

Using Multiple Group Modeling to Test Moderators in Meta-Analysis.

  Alexander M. Schoemann

Using Moderated Nonlinear Factor Analysis (MNLFA) to Develop a Commensurate Measure of Alcohol Use Across Four Independent Studies.

  Jennifer L. Walsh, Lance Weinhardt, Seth Kalichman, & Michael Carey

Session 2.3

Small Sample Robust Model Fit Criteria in Latent Growth Models with Non-Informative Dropout.

  Dan McNeish & Jeff Harring

Growth Modeling with Selection and Missing Data: A Shared-parameter Model for Predicting College Readiness with Interim Assessment Results.

  Yeow Meng Thum & Tyler Matta

Session 2.4

Comparing Aspects of Data Collection to Improve Statistical Power.

  Andrew L. Moskowitz, Jennifer L. Krull, K. Alex Trickey, & Bruce F. Chorpita          

Partially Nested Randomized Control Trials in Educational Research: Applications to a Summer Learning  Program.

Jonathan Schweig & John Pane

Predicting Group-Level Outcome Variables:  An Empirical Comparison of Analysis Strategies.

Jeffrey D. Kromrey & V. Lynn Foster-Johnson

Session 2.5

A Study of Classroom Learning with a Mixed Model for Ordinal Variables and Special Emphasis on Individual Differences.

  Robert Cudeck

 A Mode of Zero: Strategies for Education Data with Cases of Zero.

Lauren Porter

Modeling Between and Within-Subject Variances Using Mixed Effects Location Scale Models for Intensive Longitudinal Data

1.    A Rasch Analysis of Math Anxiety Scale across Cultures.

  Menglin Xu

2.    A Bayesian method to determine intrinsic item response functions in cognitive diagnostic models.

  Diego A. Luna-Bazaldua & Lawrence DeCarlo                  

3.    A Comparison of Different Methods of Zero-inflated Data Analysis.

  Si Yang, Lisa Harlow, Gavino Puggioni, & Colleen Redding

4.    A Typology of Cyber-victimization and Traditional Victimization: A 3-Step Latent Profile Analysis.

  Diana Mindrila, Pamela Davis, & Lori Moore        

5.    Techniques for Small-Sample, Longitudinal Research: Comparing Linear Mixed Effects Models and Generalized Estimating Equations.

  Chelsea Muth, Karen L. Bales, Katie Hinde, Nicole Maninger, Sally P. Mendoza, & Emilio Ferrer

6.    An Illustration of the Advantages of the Visual Analog Scale.

  Pavel Panko, Brittany K. Gorrall, Todd D. Little, Jacob D. Curtis, & Esteban Montenegro      

7.    Application of Multiple-Groups Confirmatory Factor Analysis to Test for Psychometric Measurement Invariance.

  Samara L. Rice, Mark A. Prince, Robert C. Schlauch, Joseph F. Lucke, & Gerard J. Connors

8.    Assessing the Performance of Single Item Longitudinal Models over Varying Conditions.

  Ruben Castaneda

9.    Autoregressive Latent Growth Modeling: A Bayesian Approach.

  Yuzhu Yang & Sarah Depaoli      

10.    Characterizing Conceptual Change with Latent Transition Analysis.

  Glen Davenport

11.  Comparing forensic DNA testing outcomes for biological evidence from stranger versus non-stranger rapes: Results from the Detroit Sexual Assault Kit Action Research Project.

  Steven J. Pierce, Dhruv B. Sharma, & Rebecca Campbell              

12.  Comparing the Gamma Generalized Linear Model, Log Transformation, and Yuen-Welch for Power and Generalizability.

  Victoria Ng & Rob Cribbie                       

13.  Comparing Traditional and Bayesian Approaches for Testing Mean Equivalence.

  Alyssa Counsell, Robert Cribbie, & Victoria Ng     

14.  Detecting Relations Among Dynamic Processes with Two-Occasion Data.

  Corinne Henk & Laura Castro-Schilo                   

15.  Determining Necessary Sample Size for Dynamic Group Models.

  Wendy Christensen & Jennifer Krull        

16.  Effects of ARMA Processes, Specification of Correlated Error, and Number of Time Points on Latent Growth Model Fit and Parameter Bias: A Monte Carlo Study.

  Daniel M. Smith

17.  Estimating Trends in River Water Temperature at Level 3 (year), Given Variable Occasion  Designs, Data Sparseness and Potential Confounders at Levels 1 And 2.

  Brian Gray

18.  Estimating Interaction Effects in Multilevel Models: A Simulation Study Examining Power and Type I Error.

  Julie Lorah

19.  Evaluating Cost-effectiveness of Community Risk Prevention Programs: Illustration of Simulating What Would Happen in other Communities.

  Maria Coman, L. Suzanne Suggs, Gisela Rots, & Emil Coman                     

20.  Evaluation of a Bayesian Approach to Estimating Nonlinear Mixed-Effects Mixture Models.

  Sarfaraz Serang, Zhiyong Zhang, Jonathan Helm,, Joel S. Steele, & Kevin J. Grimm 

21.  How to Find Confidence Interval for CFI and RMSEA using Bootstrap.

  Xijuan Zhang & Victoria Savalei              

22.  In the Eye of the Beholder: Is Perceived Similarity a Product of the Individual or the Dyad?

  Sonya M. Stokes, Bobbie A. Dirr, & Paras Mehta

23.  Is Multivariate Technique Necessary: Estimating the Effects of Moderated Multiple Regression Under Ols Framework.

  Dingjing Shi & Ji Hoon Ryoo       

24.  Items that Hang Together may not Change Together: Exploring Dimensions of Change in Sense of Identity.

  Thai Ong & Monica Erbacher

25.  Making Causal Inferences Using Education Observational Data with Multilevel Data Structures.

      Jose M. Hernandez

26.  Parental Harshness and Warmth and Cognitive Outcomes in Hispanic American, African American and European American Families.

  Elif Dede Yildirim & Jaipaul L. Roopnarine            

27.  Rasch Model Parameter Estimation via The Elastic Net.

  Jon-Paul Paolino

28.  Similar Fit Statistics and Similar Partitions: How Selecting a Suboptimal Solution Impacts the Accuracy of a Mixture Model.

  Emilie Shireman

29.  The Impact of Linear Dependence on Latent Variable Modeling.

  Fraser Bocell

30.  The New Methods for Detecting Aberrant Behavior In Educational Testing.

  Kaiwen Man & Yunbo Ouyang    

31.  Treatment of Missing Values in Classification and Regression Tree Analyses.

  Shu Xu, Natalie Rubinchik, & Michael F. Lorber    

32.  Type-I Error Rates and Power of Three Robust Chi-Square Difference Tests When Evaluating Measurement Invariance.

  Jordan Brace, Victoria Savalei, & Jenny Chuang   

33.  Variable Selection for Propenstity Score Matching on Prognostic Strata.

  Jiaqi Zhang & Chrispother M. Swoboda

Session 3.1 – Symposium

Methods for Analyzing Secondary Outcomes in Public Health Case-Control Studies.

Ofer Harel (Chair), Elizabeth D. Schifano, & Haim Bar        

Session 3.2

Introducing N-Level Structural Equations Modeling: Framework, Software and Applications.

Paras D. Mehta

Session 3.3

Comparison of Advanced Methods for Data Imputation in the Context of Item Response Theory: A Monte Carlo Simulation.

 Julianne M. Edwards & W. Holmes Finch  

Multidimensional Item Calibration and Plausible Value Imputation in Large-Scale Educational Assessments using the Metropolis-Hastings Robbins-Monro Algorithm.

Lauren Harrell & Li Cai    

Session 3.4

A Methological Illustration for Regression Mixture Models: Current Issues Of Estimation Problems.

 Minjung Kim, Andrea Lamont, & M. Lee Van Horn            

Session 3.5

Reconciling Factor-Based and Composite-Based Approaches to Structural Equation Modeling.

 Edward E. Rigdon

Session 4.1- Symposium

The “What”, “Why”, and “How” of Partial Approximate Measurement Invariance.

Chair: Katherine Masyn & Julia Higdon     

Paper 1: Navigating the Full-No Measurement Invariance Passage with Partial Approximate Measurement Invariance.

Paper 2: Partial Approximate Measurement Invariance in Action: Measuring Intergroup Attitudes in Europe.

Session 4.2

Row Fit Derivative Clustering for Heterogeneity Analysis.

Timothy R. Brick

The Method of State Space Mixures.

Michael D. Hunter

Session 4.3

Using Autoregressive Fractional Integrated Moving Average (ARFIMA) Models to Analyze Daily High School Attendance over the Long Term.

Matthijs Koopmans

Mediational Processes in Latent Growth Curve Modeling: Investigation of the Longitudinal Effect of Technology-Based Substance Use Treatment on Drug Abstinence.

Sunny Jung Kim, Lisa A. Marsch, & Haiyi Xie         

Analyzing Long-duration and High-frequency Data Using the Time-varying Effect Model.

Haiyi Xie, Robert E. Drake, Sunny Jung Kim, & Gregory J. McHugo

Session 4.4

Detailed Effect Analysis Using Structural Equation Modeling.

Axel Mayer, Lisa Dietzfelbinger, Yves Rosseel, & Rolf Steyer

Structural Equation Models for Comparing Dependent Means and Proportions.

Jason T. Newsom

Session 4.5

A Guide to the Application of Multilevel Structural Equation Modeling: Bayesian and Frequentist Implementations.

James P. Clifton & Sarah Depaoli  

Impact of Serial Correlation Structures on Random Effect Misspecification with the Linear Mixed Model.

Brandon LeBeau

Robust Bayesian Methods in Growth Curve Modeling.

Xin Tong & Zhiyong Zhang                       

Session 4.6

Comparing the Performance of the Mean- and Variance-Adjusted ML Chi-Square Test Statistic with and without Satterthwaite df Correction.

Jonathan M. Lehrfeld & Heining Cham

Robust Joint Modelling: Questioning the Distributional Assumptions.

Lisa McCrink, Adele Marshall,  Karen Cairns, & Damian Fogarty      

Two F Approximations to the Distribution of Test Statistics in SEM.

Hao Wu & Johnny Lin      

Session 4.7

Errors-in-variables System Identification using Structural Equation Modeling.

David Kreiberg

New Variable Selection Criteria in Model Selection.

Ji hoon Ryoo, Snigdhansu Chatterjee, & Dingjing Shi

Single Session 5.1

Confirmatory Composite Analysis – Making Structural Equation Modeling Fit for Design Research.

 Jörg Henseler

Single Session 5.2

Context Questionnaire Rotation and Imputation with Implications for Estimation of Plausible Values in Large-Scale Assessments.

 David Kaplan & Dan Su

Group Session 5.3

Estimating Latent Variable Interactions with Incomplete Exogenous Items.

 Heining Cham & Evgeniya Reshetnyak     

Performances of Mixture Latent Moderated Structural Equations Approach.

Evgeniya Reshetnyak & Heining Cham     

Group Session 5.4

Using a Scale-Adjusted Latent Class Model to Establish Measurement Equivalence in Cross-Cultural Surveys: An Application with the Myers-Briggs Personality Type Indicator (MBTI).

Jay Magidson

Simultaneous Two-Way Fuzzy Clustering of Multiple Correspondence Analysis.

Sunmee Kim & Heungsun Hwang 

Session 5.5

Are Indirect Effects Better Captured by Multiple Group Analyses? Benefits of Multiple-Group Structural Modeling in Testing Causal Mediation.

Emil Coman, Judith Fifield, & Monique Davis-Smith            

Comparing Recent Advances in Causal Mediation: How Medical Researchers and Practitioners Can Better Understand Causal Mediation and use it for Personalized Medicine.

Emil Coman & Judith Fifield                                  

Session 6.1 – Symposium

Applications of Advanced Latent Variable Modeling in the Study of Reading and Motivation.

Chair: Paulina Kulesz

Paper 1: Evaluating the Impact of Common Method Variance in a SEM Model of Reading Comprehension.

Yusra Ahmed, David J. Francis, Jack M. Fletcher, Mary York, & Marcia A. Barnes

Paper 2: Measuring Motivation to Read Through Self-Report: New Insights Through the Application of Polytomous Item Response Models.

Paulina A. Kulesz, David J. Francis, Mary York, and Chris A. Wolters

Paper 3: An Application of Explanatory Item Response Models to Study Developmental Changes in Reading and Visual Processing Skills in Grades K-2.

Shiva Khalaf, Paulina A. Kulesz, Kristi L. Santi, & David J. Francis

Session 6.2 – Symposium

Validating Methods for Predicting Individual Treatment Effects.

 Chair: Andrea Lamont

Paper 1: An imputation-based approach for predicting individual treatment effects.

Andrea Lamont, Mike Lyons, & Lee Van Horn

Paper 2: A random forest approach to predicting individual treatment effects.

Mike Lyons, Andrea Lamont, & Lee Van Horn

Paper 3: Sample size requirements for imputation-based PITE.

Kathleen Jocoy, Andrea Lamont, & Lee Van Horn

Session 6.3

Because it Might not Make a Big Dif: Improved Differential Test Functioning Measures.

David B. Flora, R. Philip Chalmers, & Alyssa Counsell         

Methods for the Comparison of DIF across Assessments.

 Holmes Finch, Maria Finch, & Brian French          

Permutation Randomization Methods for Testing Measurement Equivalence and Detecting Differential Item Functioning.

 Terrence D. Jorgensen, Benjamin A. Kite, Po-Yi Chen, & Stephen D. Short  

Session 6.4

Checking Robustness of Longitudinal Results Across Two Types of Gain Scores.

— Handout —

 Robert E. Larzelere, Mwarumba Mwavita, Taren Swindel, Ronald Cox, Jr., & Isaac Washburn 

Three Steps Toward Improving Causally Relevant Conclusions from Longitudinal Studies.

Robert E. Larzelere, Ronald B. Cox, Jr., & Taren Swindle    

Session 6.5

“To Parcel or Not to Parcel” 2.0: Parceling Indicators in Latent Class Models.

 Katherine Masyn & Todd Little

A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

 Ji Yeh Choi & Heungsun Hwang  

Feasible Sample Size Determination in Confirmatory Factor Analysis

Jennifer Koran

Session 6.6

Confidence Sets and Exchangeable Weights in Multiple Linear Regression.

Jolynn Pek & R Philip Chalmers    

OLS and HCSE Estimation in Linear Models: An Investigation of Non-normality, Heteroscedasticity, and Measurement Error.

 Lynn Foster-Johnson & Jeffrey D. Kromrey          

Thomas Cook, Ph.D.

Bigger Data and Stronger Causal Inferences from Quasi-

Experimental Data

Post-conference Workshop

Multilevel Structural Equation

Modeling using xxM

Paras Mehta

University of Houston