2013 Keynotes and Paper Presentations

8:45 – 10:15 am Keynote Address: Linda Collins, Ph.D.Optimizing behavioral interventions:  An integration of methodological perspectives from the behavioral and engineering sciences
10:30 – 12:00 pm CONCURRENT SESSION #1Combined Session 1.1: Quantifying Uncertainty in Structural Equation Modeling

Accounting for Population Uncertainty in Covariance Structure Analysis by Hao Wu, and Michael W. Browne

Parameter Uncertainties in Structural Equation Modeling: Quantification and Implications by Taehun Lee, Robert MacCallum, and Michael Browne

Profile Likelihood-Based Confidence Regions in Structural Equation Models by Jolynn Pek, and Hao Wu

Combined Session 1.2:  Longitudinal Fit and Invariance

Assessment of Fit Indices for the Determination of Measurement Invariance in Longitudinal Models by Corbin T. Quick, Aaron J. Boulton, Alexander M. Schoemann, and Todd D. Little

Are You Measuring Variability or Trait Change? On the Role of Measurement (Non)Invariance in Latent State-Trait Analyses by Christian Geiser, Brian T. Keller, Ginger Lockhart, Michael Eid, and Tobias Koch

Models of Variability versus Models of Trait Change: How Well Do Fit Indices Distinguish Between the Two? by Brian T. Keller and Christian Geiser

Combined Session 1.3: Missing Data Methods

A comparison of imputation strategies to missing ordinal item scores by Wei Wu, Craig Enders, and Fan Jia


Using principal component analysis (PCA) to obtain auxiliary variables for missing data estimation in large data sets by Waylon J. Howard  and Todd D. Little


Missing Data Methods for Confounding Variables in Marginal Structural Models by Shu Xu and Vanessa Watorek, New York University

Combined Session 1.4: Analyzing Single Subject, Diary, and Intensive Longitudinal Data

Daily Diary Data: Effects of Cycles on Inferences by Yu Liu and Stephen G. West

Modeling Cyclical Patterns in Daily College Drinking Data with Many Zeroes by David Huh, Debra L. Kaysen, and David C. Atkins

The Misspecification of the Covariance Structures in Multilevel Models for Single-Case Data: A Monte Carlo Simulation Study by Mariola Moeyaert, Maaike Ugille, John M. Ferron, S. Natasha Beretvas, and Wim Van den Noortgate (Presented by Patricia Rodriguez)

Combined Session 1.5: Profile Analysis and Non-normal SEM

Modeling Configural Patterns in Latent Variable Profiles Associated with Endogenous Criteria by Mark Davison, Ernest Davenport, and Yu-Feng Chang

Moderated Profile Analysis: Comparing Criterion-Related Predictor Variable Patterns across Populations by Mark Davison, and Ernest Davenport

Investigation of Type I Error Rates of Three Versions of Robust Chi-Square Difference Tests byVictoria Savalei, Jenny Chuang, andCarl Falk

Combined Session 1.6: Propensity Score Analysis

The Impact of Measurement Error on Propensity Score Analysis: An Empirical Investigation of Fallible Covariates by Eun Sook Kim, Patricia Rodriguez de Gil, Jeffery D. Kromrey, Aarti P. Bellara, Rheta E. Lanehart, Tyler Hicks, and Reginald S. Lee

Propensity Score Matching (with multilevel data) Using SPSS and R by Felix Thoemmes, and Wang Liao

1:30 – 3:00 pm CONCURRENT SESSION #2Session 2.1: Open-source Modern Modeling Software: The R Package Lavaan by Yves Rosseel

This is a double session which runs through concurrent sessions 2 and 3

Combined Session 2.2: Extensions to Growth Models

Multiple-Indicator Latent Growth Curve Models: An Analysis of the Second-Order Growth Model and Two Less Restrictive Alternatives by Jacob Bishop and Christian Geiser

The Autoregressive Latent Trajectories Model:  An Alternative Approach to the Analysis of Panel Data by Chris Schatschneider


Recovery of Individual Trajectories in Heterogeneous Samples Using Longitudinal Latent Profile Analysis (LLPA) by Veronica T. Cole & Daniel Bauer


Combined Session 2.3: Stepwise Approaches to Latent Variable Modeling

Group means as explanatory variables in multilevel modelsbyJouni Kuha, Anders Skrondal and Stephen Fisher


The  bias-adjusted three-step approach to latent class modeling with external variables by Zsuzsa Bakk, Daniel Oberski, and Jeroen K. Vermunt


Three step Latent Transition Analysis by Bengt Muthen and Tihomir Asparouhov


Three-step estimation method for discrete micro-macro multilevel models byMargot Bennink, Marcel A. Croon, and Jeroen K. Vermunt


Combined Session 2.4: New Developments in the Analysis of Incomplete Data Symposium

Utilizing Hyper Priors in Multiple Imputation for Multivariate Normal Databy Valerie Pare


Handling Data with Three Types of Missing Values: A Simulation Study by Jen Boyko


Approaches to Multiple Imputation in large data setsby Chantal Larose


Combined Session 2.5: Measurement Invariance and Differential Item Functioning

A Simulation Study of a MIMIC-based Strategy for Detecting Items with DIF by a School Covariate by Shonte Stephenson, and Sophia Rabe-Hesketh

Testing for Measurement Invariance with Respect to an Ordinal Variable by Edgar Merkle, Jinyan Fan, and Achim Zeileis

Model Invariance Testing Under Different Levels of Invariance by Holmes Finch and Brian French

Combined Session 2.6: Comparing Analyses Predicting Simple Versus Residualized Change Scores

Toward Understanding Discrepant Results from Predicting Residualized versus Simple Change Scores by Robert E. Larzelere, Ronald B. Cox, Jr., and Sada J. Knowles

Modeling Change as a Residual Difference Score or as a Simple Gain Score: Further Clarifying the Paradox by Todd D. Little, Alexander M. Schoemann, and Matthew W. Gallagher

Comparing Change Scores with Lagged Dependent Variables in Models of the Effects of Parents’ Actions to Modify Children’s Problem Behavior by David Johnson

Combined Session 2.7: Advances in Structural Equation Modeling

An Efficient State Space Approach to Estimate Univariate and Multivariate Multilevel Regression Models by Fei Gu, Kristopher J. Preacher, and Wei Wu

A Place for Nonlinear Structural Equation Modeling; What Insight Does It Give Us? by Jonathan Brewster and Kathleen Buse  

Combined Session 2.8: Extensions to Mediational Analyses

Flexible Mediation Analysis in the Presence of Non-linear Relations by Beatrijs Moerkerke, Tom Loeys, Olivia De Smet, Ann Buysse, Johan Steen, and Stijn Vansteelandt

Modeling Indirect Effects with Multimethod Data by Ginger Lockhart, Christian Geiser, Hui Qiao, Jacob Bishop, Martin Schultze, and Herbert Scheithauer

Testing Mediation the Way it Was Meant to be: Changes Leading to Changes then to Other Changes. Dynamic Mediation Implemented with Latent Change Scores by Emil Coman, Eugen Iordache, and Maria Coman



3:15 – 4:45 pm CONCURRENT SESSION #3Session 2.1 CONTINUED: Open-source Modern Modeling Software: The R Package Lavaan by Yves Rosseel

This is a double session which runs through concurrent sessions 2 and 3

Combined Session 3.2: Longitudinal Mixture Models

Using Mixture Latent Markov Models for Analyzing Change with Longitudinal Data by Jay Magidson, Statistical Innovations Inc.

A Framework for Investigating the Performance of Latent Growth Mixture Models by Paul Dudgeon

Combined Session 3.3: Planned Missing Data Designs for Longitudinal Research

Planned Missing Data Designs with Small Samples: How Small is Too Small by Alexander M. Schoemann, Fan Jia, E. Whitney G. Moore, Richard Kinai, Kelly Crowe, and Todd D. Little

Assignment Methods in Three-Form Planned Missing Designs by Terrence D. Jorgensen, Alexander M. Schoemann, Brent McPherson, Mijke Rhemtulla, Wei Wu, and Todd D. Little

Planned Missing Designs to Optimize the Efficiency of Latent Growth Parameter Estimates by Fan Jia, Mijke Rhemtulla, Wei Wu, Todd D. Little

Two-method Planned Missing Designs for Longitudinal Research by Mauricio Garnier-Villarreal, Mijke Rhemtulla, and Todd D. Little

Combined Session 3.4: Multidisciplinary Perspectives on Fit

Comparing the Evidence for Categorical Versus Dimensional Representations of Psychiatric Disorders in the Presence of Noisy Observations: A Monte Carlo study of the Bayesian Information Criterion and Akaike Information Criterion in latent variable models by Michael Hallquist, Thomas Olino, andPaul Pilkonis

The Effects of Local Item Dependence on the Sampling Distribution of the Q3 Statistic by William P. Skorupski, andSukkeun Im

Bootstrapping SEM Goodness of Fit and Confidence Intervals by Craig M. Krebsbach, and Lisa L. Harlow

Combined Session 3.5 Multilevel Survival Analysis

Modeling Microsocial Heterogeneity using multilevel survival analysis by Mike Stoolmiller

Continuous Time Analysis of Panel Data: An Illustration of the Exact Discrete Model by Aaron J. Boulton, and Pascal R. Deboeck

Combined Session 3.6: Extensions to Factor Analysis

Multilevel Factor Analysis by Model Segregation: The Surprising Necessity for Robust Statistics with Normal Databy Jonathan Schweig


The Influence of Parceling on the Implied Factor Structure of Multidimensional Data by Brooke Magnus, and Yang Liu


To Thin or Not To Thin? The Impact of Thinning Posterior Markov Chains on Parameter Estimation in Latent Trait Modelsby Jared K. Harpole, and William P. Skorupski


Session 3.7: Introduction to Quantile Regression for Social Science Researchers

Introduction to Quantile Regression for Social Science Researchers by Jessica Logan and Yaacov Petscher





8:45 – 9:45 am CONCURRENT SESSION #4Combined Session 4.1: Meta-analysis

Individual Participant Data Meta-Analytic Modeling Techniques 1993 – 2012: A Methods Review by Samantha A. Russo, andTania B. Huedo-Medina


Measurement Harmonization in Individual-Participant-Data Meta-Analytic Modeling by Tania B. Huedo-Medina, Francisco Galindo-Garre, andMaria Dolores Hidalgo


Combined Session 4.2: Statistical Disclosure Limitation

Application of Mixture Models in Statistical Disclosure Limitation by Anna Oganian

Assessing the Privacy of Randomized Vector-valued Queries to a Database Using the Area Under the Receiver-operating Characteristic Curve by Gregory Matthews


Session 4.3: Bayesian Analysis of Dynamic Item Response Models in Educational Testing

Bayesian Analysis of Dynamic Item Response Models in Educational Testing by Xiaojing Wang, James O. Berger, andDonald S. Burdick

Session 4.4 Bias in Missing Data Problems due to Inclusion of Auxiliary Variables

Bias in Missing Data Problems due to Inclusion of Auxiliary Variables by Felix Thoemmes

Combined Session 4.5: New Developments in Model Selection Procedures

F-tests with Incomplete Data for multiple regression set-up  by Ashok Chaurasia

Model Selection for Correlated Predictors of Correlated Outcomes with Applications in Genetic Association Studies by Elizabeth D. Schifano

Combined Session 4.6: Actor Partner Interdependence Model and Extensions

Modeling Psychological Subgrouping using Multiple Demographic Composition Variablesby Randi L. Garcia

Interdependent Households Preferences – Case III/APIM Approach by Adam Sagan

Combined Session 4.7: Multilevel Analysis

Doubly-Diminishing Returns:  An Empirical Investigation of the Impact of Sample Size and Predictor Prevalence on Point and Interval Estimates from Two-Level Linear Models byBethany A. Bell, Jason A. Schoeneberger, Elizabeth A. Leighton, Stan Haines, Mihaela Ene, Whitney Smiley, andJeffrey D. Kromrey

Analyzing Clustered Data with Single-Level Models: Are Robust Standard Errors an Adequate Solution? by Dan McNeish and Jeffrey Harring

10:00 – 12:00 pm Keynote Address: Judea Pearl, Ph.D.What on earth are we modeling? Data or Reality? Reflections on structural equations, external validity, heterogeneity and missing data
1:30 – 3:00 pm CONCURRENT SESSION #5Symposium  Session 5.1: Causal Mediation

Recent advances in causal mediation by Felix Thoemmes

Misclassification of a binary mediator – effects and remedies by Linda Valeri

What Mathematics Tells us About the Mediation Formula and Why it Matters for Policy Analysis and Scientific Understanding by Judea Pearl

Combined Session 5.2: Longitudinal Models

Fitting Nonlinear Latent Growth Curve Models with Individually-varying Time Points by Sonya Sterba

Evaluating the Prediction of Growth Factors Under Misspecification of Functional Form by Stephanie Lane and Patrick Curran

Combined Session 5.3: Statistics and Modeling

Data Analysis Strategies for High Dimensional Social Science Data:  What to do when there are more variables than subjects by Holmes Finch, Maria Hernandez Finch, David E. McIntosh, and Lauren Moss

Extending the Robust Means Modeling Framework by Alyssa Counsell, Matthew Sigal, Philip Chalmers, andRobert A. Cribbie

Using Monte Carlo simulations to Understand Probabilities and Modeling: Bringing causality into the teaching of introductory statistical modeling by Emil Coman, Maria Coman, Eugen Iordache, Lisa Dierker, andRussell Barbour

Combined Session 5.4: Multiple Raters

Approximate Measurement Invariance in Rater-mediated Assessments: A Random Item Effects Item Response Model for Measuring Teaching Quality with Classroom Observations by Ben Kelcey, Dan McGinn, and Heather Hill

Level-Specific and Multilevel Reliability by Joseph A. Olsen

Reliability and Validity by the Multiple Indicator by Multiple Trait by Multiple Source by Multiple Occasion Model:  Application to an ADHD Rating by Scale by G. Leonard Burns, Mateu Servera, and Christian Geiser

Combined Session 5.5: Educational and Health Related Applications

Realistic Models for School-based Longitudinal Sociometric Data: Multilevel Cross-classified Poisson and Negative Binomial Approaches by Richard A. Faldowski, and Heidi Gazelle

A Mathematical Evaluation of the Effect of Disclosure on HIV Transmission Rate in Men who Have Sex with Men byAnn A. O’Connell, Sandra J. Reed, andJulianne M. Serovich

Patterns of Drug use Measured using Latent Class and Latent Transition Analysis with Covariates in a representative sample of Incarcerated adults in Puerto Rico by Rafael R. Ramirez, Carmen Rivera Medina, Jose Noel Caraballo, Jose Ruiz Valcarcel, Glorimar Caraballo Correa, andCarmen Albizu

Ordinal Regression Analysis: Fitting Stereotype Logistic Regression Models to Educational Data by Xing Combined Session 5.6: Understanding Patterns, Variations, And Trends In Adolescent And Young Adult Smoking: Opportunity For New Insights Or Source For Headaches?

Smoking patterns in first year college students: Trends, correlates and outcomes by Bettina B. Hoeppner and Nancy P. Barnett

Decisions about Covariate Specification in Time-Varying Effects Models: Does it Matter? by Jennifer S. Rose, Arielle S. Selya, Lisa C. Dierker, Donald Hedeker, and Robin Mermelstein

Nicotine Dependence-Varying Effects of Smoking Events on Momentary Mood Changes among Adolescents by Arielle Selya, Nicole Updegrove, Lisa Dierker, Jennifer Rose, Xianming Tan, Donald Hedeker, Runze Li, and Robin Mermelstein

A Bivariate Location-Scale Mixed-Effects Model with Application to Mood Variation among Youth Smokers by Oksana Pugach, Donald Hedeker, Robin and Mermelstein

3:15 – 4:45 pm Keynote Address: Bengt Muthen, Ph.D.Late-breaking News: Some Exciting New Methods!

Mplus Automation