Tuesday, May 20^th

Bengt Muthén, Ph.D.

Advances in Mixture Modeling

Session 1.1: Multitrait-Multimethod Models

Neglect the Structure of Multitrait-Multimethod Data at your Peril: Implications for Associations with External Variables.

Laura Castro-Schilo, Keith F. Widaman, &  Kevin J. Grimm

Uncrossing the Correlated Trait-Correlated Method Model for Multitrait-Multimethod Data.

Laura Castro-Schilo, Kevin J. Grimm, &  Keith F. Widaman

Bayesian Versus Frequentist Estimation of Multitrait-Multimethod Confirmatory Factor

Models.

 Jonathan L. Helm & Laura Castro-Schilo

Session 1.2: Individual-Participant-Data Meta-Analytic Modeling: Measurement Challenges & Network Analysis

Modeling Network Individual Data Meta-Analysis.

 Tania B. Huedo-Medina, Argie Veroniki, & Dylan Yaworski

Generalized Linear Modeling to Integrate Measures in Individual-Participant-Data Meta-Analysis.

Nathan Lally, Xiaoran Li, Francisca Galindo-Garre,  Maria Dolores Hidalgo, & Tania B. Huedo-Medina

Response Conversion Under Item Response Theory when Conducting Individual-Participant-Data Metaanalysis.

Xiaoran Li,  Nathan Lally, Francisca Galindo-Garre, Maria Dolores Hidalgo, & Tania B. Huedo-Medina

Session 1.3: Practical Issues in Missing Data Analysis

You Shall Combine, But How? A Comparison of Methods to Combine Chi-Square Using Multiple Imputation.

 Mauricio Garnier-Villarreal, Alexander M. Schoemann, & Todd D. Little

What to do with Incomplete Nominal Variables?  A Comparison of Recommended Techniques for Creating Multiple Imputations of Unordered Factors.

 Kyle M. Lang

Modeling Practice Effects Using a Three-Form Planned Missing Data Design.

Terrence D. Jorgensen, Mijke Rhemtulla, Alexander Schoemann, Brent McPherson, Wei Wu, & Todd D. Little

A Proof-of-Concept Simulation of the Accelerated Longitudinal Planned Missing Design for Latent Panel Modeling.

Luke McCune

Session 1.4: Bayesian and Simulation

Bayesian Outlier Detection in Structural Equation Models.

 Davood Tofighi

Comparative Study of Two Calibration Methods for Micro-Simulation Models.

 Stavroula Chrysanthopoulou

Testing Applications of Bayesian Statistics with Informed Priors in Multilevel Analysis of Small Data Sets with Complex Structures: A Monte Carlo Study.

Tyler Hicks, George MacDonald, Jeff Komrey, Eun Sook Kim, Jeanine Romano, & Sandra Archer

Session 1.5: Issues in Latent Class Analysis

Identifying the Correct Number of Classes in Latent Profile Analysis:  The Impact of Sample Size, Profile Distribution, and Model Specification.  

 Sara K. Johnson

Obtaining Meaningful Latent Class Segments with Ratings Data by Adjusting for Level, Scale and Extreme Response Styles.

  Jay Magidson

Session 1.6: Causal Modeling

Empirical Tests of Directional Dependence using Real Datasets.

Felix Thoemmes, Sarah Moore, & Marina Yamasaki

How do we Combine Two Treatment Arm Trials with Multiple Arms Trials in Ipd Meta-Analysis? An Illustration with College Drinking Interventions.

 David Huh, Eun-Young Mun, & David C. Atkins

Adjusting for Selection Bias in Assessing the Relationship Between Sibship Size and Cognitive Performance.

 Gebrenegus Ghilagaber & Linda Wänström

Session 2.1

Discrete and Continuous Time Models from the Perspective of Structural Equation Modeling.

  Pascal R. Deboeck & Aaron M. Boulton

Session 2.3

Testing the Homogeneity of Variance Assumption: An Investigation of the Performance of Ten Different Approaches in One-Factor ANOVA Models.

  Harold Holmes, Patricia Rodriguez de Gil, Issac Li, Aarti Bellara, Yi-Hsin Chen, Tyler Hicks, & Eun Sook Kim

Session 2.4

Bayesian Model Averaging for Propensity Score Analysis.

 David Kaplan & Jianshen Chen

Session 2.5: Advanced Longitudinal Modeling Techniques

Using a Random-Effects Tobit Model to Analyze Longitudinal Data with a Large Proportion of Zeroes.

 Haiyi Xie, Gary R.Bond, Robert.E. Drake, & Gregory J. McGugo

Investigating Differential Changes using Mixture Latent Change Scores (MLCS) Modeling.

  Emil Coman, Judith Fifield, Jack J. McArdle, & Monique Davis-Smith

Session 3.1: Explanatory Item Response Theory Models

The Effects of Reader’s Characteristics, Text Genre, and Comprehension Processes on Reading Comprehension.

 Paulina Kulesz, David Francis, Marcia Barnes, Jack Fletcher, Amy Barth, & Mary York

Reader and Text Characteristic’s Contribution to Inferential Processing in Adequate and Struggling Comprehenders.

 Yusra Ahmed, David Francis, Marcia Barnes, Jack Fletcher, Amy Barth, & Mary York

A Diagnostic Cognitive Model (DCM) of Algebraic Processing.

Justin Neil Young, Tammy D. Tolar, David J. Francis, & Jeffrey J. Morgan

Session 3.2: Exploring the lavaan Ecosystem: Packages to Extend the Capability of lavaan

semTools: Useful Tools for SEM.

Alexander M Schoemann, Sunthud Pornprasertmanit, & Patrick J. Miller

Getting the Most out of your Family of Data with the R-package fSRM.

 Lara Stas, Felix Schönbrodt, & Tom Loeys

semPlot: Unified Visualizations of Structural Equation Models.

Sacha Epskamp

lavaan.survey.

Daniel Oberski

simsem: SIMulated Structual Equation Modeling in R.

 Sunthud Pornprasertmanit, Alexander M. Schoemann, Patrick J. Miller

Graphical Structural Equation Modeling with Onyx.

Timo von Oertzen, Andreas Brandmaier, &  Siny Tsang

Session 3.3: New Developments in the Analysis of Incomplete Data

A Survey of Missing Data Techniques Employed in Genome-Wide Association Studies.

 Gregory J. Matthews & Ofer Harel.

Clustering Incomplete Data using Normal Mixture Models.

Chantal D. Larose, Ofer Harel, & Dipak Dey

Comparison of Transformations used in the Estimation of R²  and Adjusted R²  in Incomplete Data Sets using Multiple Imputation.

Valerie Pare & Ofer Harel

Session 3.4: Bayesian Modeling

Bayesian SEM Perspectives (From the Hills of Asymptotia).

 Albert Satorra

Bayesian Estimation for Structural Equation Models with Sample Weights.

 Bengt Muthen

Bayesian Analysis of Multiple Indicator Growth Modeling using Random Measurement Parameters Varying Across Time and Person.

 Tihomir Asparouhov

Session 3.5: Modeling Treatment and Causal Effects

Treatment Effects in Randomized Controlled Trials with Noncompliance and Missing Data.

 Shu Xu, Michael F. Lorber, Amy M. S. Slep, Richard E. Heyman, & Danielle M. Mitnick

Estimation of Heterogeneity of Treatment Effect using EM Algorithm.

 Evgeniya Reshetnyak, Ying Liu, Barry Rosenfeld, & William S. Breitbart

Probing Causal Mechanisms and Strengthening Causal Inference by Means of Mixture Mediation Modeling.

 Emil Coman, Judith Fifield, Suzanne Suggs, Deborah Dauser-Forrest, & Martin-Peele Melanie

Session 3.6: Modeling and Mediation

Parametric Sensitivity Analysis Thresholds for Mediation Effects.

 Ben Kelcey, Kenneth Frank, & Michael Seltzer

The Markov Equivalence Class of the Mediation Model. 

 Felix Thoemmes, Wang Liao, & Marina Yamasaki

Mediation Analysis in AB/BA Crossover Studies. 

 Haeike Josephy, Tom Loeys, & Stijn Vansteelandt

James Robins, Ph.D.

Estimation of Causal Effect of Exposures that Change Over Time: Methods and Case Studies.

Wednesday, May 21^st

Sophia Rabe-Hesketh, Ph.D. 

Simple Methods for Handling Non-Randomly Missing Data.

Session 4.1: New Developments in Variable Selection for Regression Models

An Introduction to Variable Selection for Regression Models.

Ofer Harel

An Empirical Bayes Approach to Variable Selection and QTL Analysis.

 Haim Bar

Model Selection Through Sparse Estimation in Finite Mixture Regression Models.

 Elizabeth D. Schifano, Robert L. Strawderman, & Martin T. Wells

Session 4.2

Factor Indeterminacy and Factor-Based Structural Equation Modeling.

Edward Rigdon

Session 4.3: Longitudinal Models

Fit Criteria Performance and Parameter Estimate Bias in Growth Curve Models with Small Samples in the SEM Framework.

 Dan McNeish

Issues in Latent Growth Modeling with Longitudinal Public-Release Data. 

 Ming Li, Jeffrey Harring, & Laura Stapleton

Session 4.4: Effect Size and Confidence Intervals

An Investigation of Accuracy and Precision of the Generalized Eta-Squared Effect Size Based on Various Research Designs.

 Patrice Rasmussen, Patricia Rodriguez de Gil, Anh Kellerman, Thanh Pham, Jeanine Romano, Yi-Hsin Chen, & Jeffrey Kromrey

Robust Confidence Intervals for Effects Sizes in Multiple Linear Regression.

Paul Dudgeon

Session 4.5: Latent Transition Analysis

Implementing the 3 Step Latent Transition Analysis in MPLUS using a Sub-Population from a Complex Sample Design.

 Rafael R Ramirez, Jose Noel Caraballo, & Carmen Rivera Medina

Session 4.6: Advanced Modeling of Healthcare Data

Hierarchical Bayesian Exploratory Factor Analysis for Health Care Quality Utilization and Quality Data.

 Alan M. Zaslavsky &  A. James O’Malley

Modeling Multilevel Data with Cross-Classified Outcome Variables using Kronecker-Structured Covariance Matrices, with Applications to Multivariate-Outcome Random-Coefficient Models for Healthcare Quality Data.

 Alan M. Zaslavsky & Laura A. Hatfield

Session 5.1: Causal Modeling in Communication

Iterative Meta-Causal Analysis: Modeling the Impact of Job Loss on Communication and Personality.

Mark Hamilton

Testing the Viability of Alternative Structures with a Distributed Computing System.

James Watt & Mark Hamilton

The Influence of Synchrony and Sensonry Modality on the Person Perception Process in Computer-Mediated Groups.

 Kristine Nowak & James Watt

Analyzing and Modeling Behavioral Interaction Data.

Arther Vanlear & Teharan Davis

Session 5.2

An Introduction to Integrative Data Analysis in the Behavioral and Social Sciences.

  Jennifer Walsh

Session 5.3

A Demonstration of a New Linear Modeling Procedure in SPSS Statistics: Automatic Linear Modeling (linear). 

Hongwei Yang

Ordinal Logistic Regression Models for Complex Sample Survey Data Using Stata, SPSS and SAS.

Xing Liu.

Session 5.4

DataToText: Consumer-Oriented Dyadic Data Analysis using R.

 David Kenny

Session 5.5: Measurement Modeling

An Investigation of the Alignment Method for Detecting Measurement Non-Invariance Across Many Groups with Dichotomous Indicators.

 Jessica Kay Flake, Erin Strauts, Betsy McCoach, Jane Rogers, & Megan Welsh

Dimensionality at Multiple Levels: Examining NAEP Mathematics with An Exploratory, Multilevel Item Factor Model.

 Nathan Dadey & Gregory Camilli

Session 5.6

Evaluating Measurement Equivalence and Translation Effectiveness of a Customer Engagement Instrument Across National Cultures and Types of Customers.

 Dan Yu & Yongwei Yang

A Mixture Model for Nuptiality Data with Long-Term Survivors.

 Paraskevi Peristera & Gebrenegus Ghilagaber

Session 6.1

A Workshop on Bayesian Nonparametric Regression Analysis.

 George Karabatsos

Presentation slides

Handouts

Session 6.2: Propensity Score Analysis: Empirical Investigations of Common Problems and their Impacts on Treatment Effect Estimates

Impact of Measurement Error in Propensity Score Analysis.

 Eun Sook Kim

Treatment of Missing Data in Propensity Score Analysis.

 Patricia Rodriguez de Gil

Single-Level vs. Multi-level Propensity Scores with Nested Data.

 Patricia Rodriguez de Gil & Jeffrey Kromrey

Covariate Balance in Propensity Score Models: Much Ado about Nothing?

 Jeffrey Kromrey

Session 6.3: Missing Data

A Systematic Approach to Search for Efficient Designs in Analysis of Change.

 Fan Jia, Wei Wu, Mijke Rhemtulla, & Todd D. Little

A Latent Variable Chained Equations Approach for Multilevel Multiple Imputation.

 Craig K. Enders & Brian T. Keller

Session 6.4: Item Response Theory

Unipolar Item Response Models.

 Joseph F.  Lucke

Robustness of Mixture Item Response Models to Two Correlated Sources of Differential Item Functioning.

 Erin Strauts & Jessica Kay Flake

Realistic IRT Item Parameter Generation for Monte Carlo Simulation Studies.

Ling Ning, Cindy Walker, & Bo Zhang

Session 6.5: Modeling Dyadic Data

Modeling Growth in Dyads at the Group Level.

 Thomas Ledermann & Siegfried Macho

A Structural Equation Model Of Dyadic Discrepancy Over Time.

 Holly Laws, Aline Sayer, Paula Pietromonaco, & Sally Powers

The Actor-Partner Interdependence Model For Categorical Dyadic Data: An Introduction to GEE.

 Tom Loeys, William Cook, Olivia De Smet, Anne Wietzker, & Ann Buysse

Session 6.6: Modeling Secondary Data

Using the Pair-Wise Likelihood Method to Analyze Large Datasets with Discrete Responses.

 Maria T. Barendse, Frans J. Oort, Marieke E. Timmerman, & Y. Rosseel

Maximum Likelihood Adjustment of Anticipatory Covariates in Analyzing Retrospective Survey Data.

 Gebrenegus Ghilagaber & Rolf Larsson

Edward Vytlacil, Ph.D.

Accounting for Individual Heterogeneity in Treatment Effect Analysis.