2015 Presentations and Keynotes PDFs

Monday, May 18th
Pre-conference Workshop

Karl Jöreskog

New Features in LISREL 9

Tuesday, May 19th
Keynote Address

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


Keynote AddressDonald Hedeker, Ph.D.

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




Wednesday, May 20th  

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          


Keynote Address

Thomas Cook, Ph.D.

Bigger Data and Stronger Causal Inferences from Quasi-

Experimental Data


Thursday, May 21st

Post-conference Workshop

Multilevel Structural Equation

Modeling using xxM

Paras Mehta

University of Houston