MMM Conference Schedule

Pre-conference- Monday, May 21, 2018- 9:00-5:00

  • Coffee, continental breakfast, and Registration
    • 8:30 AM – 9:00 AM- Laurel Hall Atrium
    • During this time, you will be able to check in for any and all workshops you may have registered for, as well as the general conference.
  • Pre-Conference Workshop: Just In Time Adaptive Interventions (Susan A. Murphy & Danny Almirall)

    • 9:00 AM – 5:00 PM in Laurel Hall (Room TBA)
    • Lunch will be provided. Note: the presenters have planned for a working lunch/discussion session.

Conference Day 1- Tuesday, May 22, 2018

  • Coffee, continental breakfast, and Registration- 7:30 a.m. – 8:30 a.m. Laurel Hall Atrium

Opening Keynote-Susan Murphy- Stratified Micro-randomized Trials with Applications in Mobile Health

Technological advancements in the field of mobile devices and wearable sensors make it possible to deliver treatments anytime and anywhere to users like you and me. Increasingly the delivery of these treatments is triggered by detections/predictions of vulnerability and receptivity.  These observations are likely to have been impacted by prior treatments. Furthermore the treatments are often designed to have an impact on users over a span of time during which subsequent treatments may be provided.  Here we discuss our work on the design of a mobile health smoking cessation study in which the above two challenges arose. This work involves the use of multiple online data analysis algorithms.   Online algorithms are used in the detection, for example, of physiological stress. Other algorithms are used to forecast at each vulnerable time, the remaining number of vulnerable times in the day. These algorithms are then inputs into a randomization algorithm that ensures that each user is randomized to each treatment an appropriate number of times per day.  We develop the stratified micro-randomized trial which involves not only the randomization algorithm but a precise statement of the meaning of the treatment effects and the primary scientific hypotheses along with primary analyses and sample size  calculations.  Considerations of causal inference and potential causal bias incurred by inappropriate data analyses play a large role throughout.

Concurrent Session 1 10:30-12:00- Laurel Hall

Session 1A: Bayesian Models

Paper Authors
Understanding Bayesian Nonparametric Methods Through Programming a Dirichlet Process Mixture Model Yuelin Li

Elizabeth A. Schofield

Bayesian Estimation for Cases of Empirical Underidentification: Examples of Multitrait-Multimethod Data Analysis Jonathan Helm

Session 1B: Approaches for Modeling Clustered Count Data

Paper Authors
Approaches for Modeling Clustered Count Data


Ann O’Connell

Jing Zhang

Session 1C: Behavioral Applications

Paper Authors
Gender differences in time varying effects of adolescent affect and suicidal ideation following discharge from psychiatric hospitalization


Leslie A. Brick

Marisa E. Marraccini

Michael F. Armey

Nicole R. Nugent

Trajectories of family formation: the effects of parental divorce in a cross national perspective


Y. (Sapphire) Han

A.C. (Aart) Liefbroer

C.H. (Cees) Elzinga

Transitions in Substance Use Patterns from Adolescence to Young Adulthood


Gabriel J. Merrin

Kara Thompson

Bonnie J. Leadbeater

 Session 1D: Symposium – Quantitative Methods for Neuroimaging

Symposium Authors
Leveraging a Between-Person Grouping Algorithm to Estimate Within-Person Brain Dynamics Adriene M. Beltz

Hailey L. Dotterer

Evaluating task-dependent brain connectivity with basis functions in GIMME


Kelly A. Duffy

Kathleen M. Gates

Jessica R. Cohen

Identifying and estimating relations within and between functional brain networks using MIIVsem and GIMME


Kathleen M. Gates

Zachary Fisher

Kenneth A. Bollen

Confirmatory Subgrouping of Functional Brain Networks in Children with ADHD


Jessica R. Cohen

Kelly A. Duffy

Stewart H. Mostofsky

Inference Equifinality: Localizing network models using the jackknife. Teague R. Henry

Jessica R. Cohen

Session 1E: Symposium – Statistical Innovations for Longitudinal Data Analysis

Symposium Authors
Sparse functional log-contrast regression with longitudinal/functional compositional covariates Ken Chen
Heavy-tailed longitudinal regression models for censored data: A robust parametric approaches Larissa A. Matos, Vactor H. Lachos, Tsung-I LinLuis,  M. Castro
Joint Principal Trend Analysis for Longitudinal High-dimensional Data Yuping Zhang, Zhengqing Ouyang
  • Lunch- 12:00-1:15 in the Student Union Ballroom

Concurrent Session 2 1:15-2:15- Laurel Hall

Session 2A: Bias Reduction Methods

Paper Authors
Toward Understanding Contradictory Methods for Reducing Selection Bias in Longitudinal Analyses Hua Lin

Robert E. Larzelere

Assessing Omitted Confounder Bias in Multilevel Mediation Models Ken Kelley

 Session 2B: Innovative Longitudinal Approaches

Paper Authors
An Alternative Nonlinear Growth Model Based on Hyperbolic Sine Function


Oyamakin Samuel Oluwafemi

Chukwu Angela Unna

Bamiduro Timothy Adebayo

Application of mixed-effect location scale model in a two-group RCT to reveal positive mean changes and decreased dispersion of abstinence attitudes in a longitudinal middle school program. Harry Piotrowski

Donald Hedeker

 Session 2C: Advances in Latent Variable Modeling

Paper Authors
Evaluation of Case Diagnostics in Latent Variable Modeling Jennifer Koran

Fathima Jaffari

Leverage-based confidence intervals for structural equation modelling. Paul Dudgeon

Mariska Barendse

Yves Rosseel

 Session 2D: Psychometrics Models

Paper Authors
How to model latent ability levels when the correct answer is unknown: a cognitive psychometric approach Zita Oravecz
A Comparison of Scoring Methods for Multiple-Choice Multiple-Select Items Using NAEP 2016 DBA data Xiaying Zheng

Young Yee Kim

Session 2E: Modeling Applications in Meta-Analysis

Paper Authors
Individual participant data meta-analysis with a causal interpretation: Application in adolescent HIV prevention Heather McGee

Daniel Gittins Stone

A Bayesian Network Meta-Analysis of the Relationship between Corruption and Educational Outcomes in the New Millennium Dandan Chen

Concurrent Session 3: 2:30-3:30pm

Session 3A: Categorical Latent Variable Models

Paper Authors
Performance of Latent Growth Curve Models with Binary Variables Jason T. Newsom

Nicholas A. Smith

Multilevel SEM for ordinal data in the ‘wide’ format approach Mariska Barendse

Yves Rosseel

 Session 3B: Text Analysis Models

Paper Authors
Using Text Mining to Identify Themes in Focus Group Data


Holmes Finch

Maria Hernandez Finch

Jill Walls

Scott Hall

Waste Not, Want Not: A Methodological Illustration of Quantitative Text Analysis


Laura Castro-Schilo

Steven A. Miller

Session 3C: Centering Predictor and Mediator Variable in Multilevel and Time-Series Models with Random Slopes

Paper Authors
Centering Predictor and Mediator Variable in Multilevel and Time-Series Models with Random Slopes Tihomir Asparouhov

Bengt Muthen

Session 3D: Modern Data Modeling Approaches

Paper Authors
Handling Missing Data in Social Network Analysis: A Comparison of Approaches


Nathan T. Abe

Elizabeth A. Sanders

Elizabeth A. Dietrich

Data Mining Techniques to Estimate Propensity Scores with Continuous Treatments Zachary K. Collier


Keynote Session- 3:45-5:00- Laurel Hall

Peter Molenaar- Alternative forms of Granger causality, heterogeneity

Alternative forms of Granger causality based on standard vector autoregressive (VAR), structural VAR and unified structural equation models are presented, including time-frequency domain extensions. The group iterative multiple model estimation (GIMME) approach is proposed as the best method to accommodate heterogeneity and avoid limitations of structural VAR modeling. A new type of VAR – hybrid VAR – is introduced to obtain a unique data-driven solution to Granger causality testing.

Poster Session and Reception 5:00-6:30- Student Union Ballroom

Conference- Wednesday, May 23, 2018

  • Coffee, continental breakfast 7:30 AM – 8:00 AM

Concurrent session 4: 8:00 am-9:00 am- Laurel Hall

Session 4A: Models for Single Case Designs

Paper Authors
Bayesian Model Averaging for Single-Case Experimental Design Effect Size Estimation


Mariola Moeyaert

S. Natasha Beretvas

Sijyn Zhang

Emily Rodabaugh

Power Estimates to Test Predictor Effects in Two-Level Modeling of Single-Case Data Diana Akhmedjanova

Mariola Moeyaert

Session 4B: Model Selection Techniques

Paper Authors
Revisiting Model Selection from Fisher’s Scientific Paradigm:  An argument against the dichotomization of evidence. Allen G. Harbaugh

Wenbin Teng

Concurrent Session 4: 9:15-10:15

Session 4C: Measurement Invariance Applications

Paper Authors
Factorial Structure of Attitudes and Social Norms Scales in Math: Testing Measurement Invariance Across Cultural Groups Sounghwa Walker

Keith Widaman

Examining the Factor Structure and Measurement Invariance of Science Attitude Items across Genders Ji Yoon Jung

Anne Traynor

Session 4D: Reproducing ANOVA Using SEM

Paper Authors
Dust Yourself Off and Try Anew: Reproducing ANOVA using SEM Jonathan Helm


Concurrent Paper Session 5: Wednesday 9:15am – 10:15am

Session 5A: Exploratory Data Analysis

Paper Presenter
Comparison of exploratory data mining approaches for understanding adolescent recovery capital


Emily A. Hennessy

Emily E. Tanner-Smith

Andrew J. Finch

Exploratory Mediation Analysis with Many Mediators


Erik-Jan van Kesteren

Daniel Oberski

Session 5B: Latent Class Tree Models

Paper Authors
Using Latent Class Trees to Classify New Students in an Adaptive Assessment Progression John P. Madura
An improved latent class (LC) paradigm to obtain meaningful segments in the presence of scale confounds: Scale Adjusted Latent Class (SALC) Tree modeling Jay Magidson

Session 5C: Modeling Single Case Designs

Paper Authors
Analysis of Single-Case Experimental Count Data Using the Linear Mixed Effects Model: A Simulation Study


Lies Declercq

Laleh Jamshidi

S. Natasha Beretvas

Mariola Moeyaert

John M. Ferron

Wilm Van den Noortgate

Belen Fernandez-Castilla

Synthesizing Single-Case Studies via Multilevel Models: Limitation of Model Complexity


Ke Cheng

Zhiyao Yi

John Ferron

Mariola Moeyaert

S. Natasha Beretvas

Wilm Van den Noortgate

Session 5D: Latent Variable Modeling

Paper Authors
Estimation and Application of the Latent Group Model


Joseph Bonito

Jennifer L. Ervin

Sarah M. Staggs

Quantifying estimation uncertainty by examination of fungible parameter estimates in SEM Jordan L. Prendez

Jeffrey R. Harring

Concurrent Paper Session 6: Wednesday 10:30am – 12:00pm

Session 6A: Educational and Social Applications

Paper Authors
Political Regulations of Sexuality: the Sexual Minorities’ Rights in European Countries Dmitrii S. Tolkachev
School performance and environmental factors among students in Kenya context: Dealing with endogeneity Mwarumba Mwavita

Simon Wagura

Getting a Clear Picture of Kindergarten Learning and Performance Ya Mo

Nell Sedransk

Session 6B: Mixture Modeling Applications

Paper Authors
Modeling of Self-Report Behavior Data using the Generalized Covariates in a Uniform and Shifted Binomial Mixture Model Holmes Finch

Maria Hernandez Finch

Cluster Effects on Parameter Estimation in Multilevel Regression Mixture Models Chi Chang

M Lee Van Horn

Session 6C: Bayesian Thinking

Paper Authors
Operationalizations of inaccuracy of prior distributions in simulation studies: implications for recommendations made for applied researchers Milica Miocevic
Towards Bayesian analogs to REML Variance Components: A Gentle Introduction for the Newcomer Jonathan Templin

Tyler Hicks

Risk ratios for contagious outcomes


Olga Morozova

Ted Cohen

Forrest W. Crawford

Session 6D: Symposium – Substance Use Focused Mediation Modeling

Symposium Authors
The Factor Structure of Self-Esteem and Its Relationship to Alcohol Use in American Indian Adolescents


Melissa R. Schick

Tessa Nalve

Natasha Prasad

Nichea S. Spillane

How do text-messaging smoking cessation interventions confer benefit? A multiple mediation analysis of Text2Quit.


Bettina B. Hoeppner

Susanne S. Hoeppner

Lorien C. Abroms

Early onset marijuana use is associated with learning inefficiencies


Randi M. Schuster

Susanne S. Hoeppner

Anne E. Evins

Jodi M. Gilman

A reinforcement sensitivity model of affective and behavioral dysregulation in marijuana use and associated problems


Noah N. Emery

Jeffrey S. Simons

Session 6E: Symposium – Recent Advanced in Online-Updating Methods for Regression-type Models Involving Big Data Streams

Symposium Authors
Online Updating of Statistical Inference in the Big Data Setting Elizabeth D. Schifano
Online Updating of Survival Analysis in the Big Data Setting Jing Wu
Proportional Hazards Tests and Diagnostics in the Online Updating Setting Yishu Xue
  • Lunch 12:00-1:00 in the Student Union Ballroom

Concurrent Paper Session 7: Wednesday 1:15pm – 2:15pm

Session 7A: Modeling Applications

Paper Authors
The longitudinal associations between substance use, crime, and social risk among emerging adults: A longitudinal within and between-person latent variables analysis Gabriel J. Merrin, Jordan P. Davis, Daniel Berry, Elizabeth D’Amico, Tara M. Dumas

Session 7B: Modeling Health Disparities

Paper Authors
Modeling health disparities with a unique combinations of 1-on-1 matching and latent difference and latent change scores Emil Coman, Christina Wilson, Alysse Melville, Judith Fifield
A methodological review of the causal role of socioeconomic determinants of health disparities Emil Coman, Shervin Assari, & Helen Wu

Session 7C: Symposium – Advances in Handling Complex Nested Data Structures in Multivariate Multilevel Models

Symposium Presenter
A New Way for Handling Student Mobility with Longitudinal Data in Educational Research Congying Sun

Audrey Leroux

Christopher Cappelli

Evaluation of a Piecewise Growth Model for Multiple Membership Data Structures


Christopher Cappelli

Audrey Leroux

David Fikis

Multilevel Latent Class Analysis for Cross-Classified Data Structures Katherine Masyn

Audrey Leroux

Session 7D: Measurement Models

Paper Authors
Comparison of the Multiple Indicators, Multiple Causes Model and Hierarchical Generalized Linear Model to Detect, Moderate, and Mediate Differential Item Functioning Kevin Krost
Dimensionality of Force Concept Inventory: The Comparison of Bayesian Item Response Models Xiaowen Liu

Eric Loken

 Session 7E: Sensitivity Analysis in Latent Growth Curve Mediation Models

Paper Authors
Sensitivity Analysis in Latent Growth Curve Mediation Models Davwood Tofighi, Yu-Yu Hsiao, Eric S. Kruger, David P. MacKinnon, M. Lee Van Horn, Katie Witkiewitz

Closing Keynote- 2:30-4:00 in Laurel Hall Room

Tenko Raykov- Item Response Theory and Classical Test Theory: Too Long Too Far

This talk is concerned with a view of item response theory that is inclusive of classical test theory rather than juxtaposing the former to the latter.  In the widely employed setting in empirical research of homogeneous binary or binary scored items with no guessing, popular item response theory models can be directly obtained from appropriately developed classical test theory based models accounting for the discrete nature of the observed items.  Two distinct (observational) equivalency approaches are pointed out that render these item response theory models from corresponding classical test theory based models, and can each be used to obtain the former from the latter models.  Similarly, classical test theory based models can be furnished utilizing the reverse application of either of those approaches from corresponding item response theory models.

Post-conference- Thursday, May 24, 2018- 9:00-5:00

 Item Response Theory from a Latent Variable Modeling framework- Tenko Raykov

  • Coffee, continental breakfast 8:30 AM – 9:00 AM
  • 9:00 AM – 5:00 PM in Laurel Hall

This one-day workshop is based on a latent variable modeling approach to item response theory (IRT) and item response modeling (IRM). The workshop commences with a non-traditional approach to IRT and IRM that is based on their essential connections to other behavioral measurement methodologies. These include classical test theory (CTT), (nonlinear) factor analysis, and logistic regression. The flaws of earlier treatments of CTT in the context of multiple IRT and IRM discussions are pointed out, which in addition to misrepresenting CTT effectively shift away research attention to more specific rather than more generally applicable modeling and analytic procedures. Resent research on the connections between classical test theory and IRT/IRM is then reviewed. Using a measurement invariance examination based approach, a multiple testing method for differential item functioning is discussed that deals with limitations of an existing widely utilized procedure. A readily applicable method for studying essential unidimensionality of multi-item measuring instruments is then obtained as a byproduct of this method. Item response models with covariates are finally discussed. Use of the popular software Mplus and Stata is made repeatedly and on a few occasions IRTPRO, flexMIRT, and R are utilized. The workshop is based on an integrative approach to measurement in the behavioral and social sciences and emphasizes throughout the links between IRT and IRM on the one hand and other measurement and modeling methodologies related to them on the other hand.

Item Response Theory: A Latent Variable Modeling Perspective Outline

0. Resources for course. Latent variables and their relevance for Item Response Theory
(IRT) and Item Response Modeling (IRM).
1. Introduction and overview of IRT/IRM.
2. An example of item response modeling.
3. Popular unidimensional IRT models.
4. Information functions.
5. Differential item functioning (DIF).
6. Introduction to multidimensional IRT/IRM.
7. Extensions and limitations of some current IRT/IRM applications.
8. Conclusion and outlook.