Conventions & Events > APS Annual Convention > 2016 Workshops

2016 Workshops

Workshops

 

*Co-sponsored by APS and the Society of Multivariate Experimental Psychology (SMEP). Separate registration is required for workshops, which are open to Convention and/or Teaching Institute registrants only.

 

Introduction to R Statistical System*

Thursday, May 26 9:00 AM – 10:50 AM

 

William R. Revelle, Northwestern University
Sara Weston, Washington University in St. Louis
David M. Condon, Northwestern University

R is an integrated suite of software facilities for data manipulation, calculation, and graphical display that is particularly useful for psychological scientists. This workshop will assume no prior knowledge of R and will emphasize standard functions for analysis and display of experimental and correlational data for classroom and research.
 

The Theory and Practice of Machine Learning in Psychology: The What, Why, and How of a Powerful Statistical Technique*

Thursday, May 26 9:00 AM – 12:20 PM

 

Matthew S. Goodwin, Northeastern University
Ryan L. Boyd, The University of Texas at Austin

One of the largest growing classes of analytic techniques is known as machine learning, a computational approach to predicting and understanding complex patterns in data. In this workshop, we will introduce core machine-learning concepts/applications and provide a hands-on tutorial with machine-learning methods.
 

Social-Relations Modeling of Dyadic Data*

Thursday, May 26 9:00 AM – 12:50 PM

 

Thomas E. Malloy, Rhode Island College

Dyadic research can address phenomena that cannot be studied with individuals, yet poses unique challenges. The Social-Relations Model (SRM) is well suited for research on a broad range of phenomena that can be studied simultaneously at the individual, dyadic, and group levels of analysis. This workshop will provide an introduction to the logic of dyadic analysis using the SRM, multiple interaction designs, the organization of data for analysis, specialized software (e.g., SOREMO, BLOCKO) for initial analyses, the interpretation of variance components and correlations from initial analyses, modeling complex phenomena following the initial social-relations analysis, and the reporting of results. The workshop is designed for those with little or no knowledge of social-relations analysis, with the goal of developing basic skills necessary to design and conduct dyadic research. Advanced statistical issues related to the SRM will not be addressed.
 

Studying Lagged Relationships*

Thursday, May 26 9:00 AM – 12:50 PM

 

Ellen L. Hamaker, Utrecht University, The Netherlands

Multivariate longitudinal data offer the opportunity to investigate how variables influence each other over time through estimating their lagged relationships. During this workshop, we will focus on crucial issues in this context, including the decomposition of within-person and between-person variance, the effects of trends, and the use of change scores.
 

Structural Equation Modeling With Lavaan*

Thursday, May 26 12:00 PM – 3:50 PM

 

Yves Rosseel, Ghent University, Belgium

This workshop offers both a refresher of structural equation modeling and a tutorial on how to use the R package lavaan. Both basic and more advanced topics will be covered, including multiple groups, measurement invariance, missing data, and nonnormal and categorical data. Bring a laptop with R and lavaan installed.
 

Mindfulness Meditation: Mechanism, Application and Practice

Thursday, May 26 1:00 PM – 2:20 PM

 

Yi-Yuan Tang, Texas Tech University

Research broadly supports the claim that mindfulness meditation exerts beneficial effects on physical and mental health and cognitive performance. Recent neuroimaging studies have begun to uncover the brain areas and networks that mediate these positive effects. However, the underlying neural mechanisms remain unclear. Here, I will discuss the mechanism, application, and practice of mindfulness meditation. The future direction will also be discussed.
 

Improving Reproducibility of Our Research Practices*

Thursday, May 26 1:00 PM – 3:50 PM

 

Brian Nosek, University of Virginia
Courtney Soderberg, Center for Open Science

This practical workshop will review laboratory and personal research practices to improve reproducibility. Topics include project and data management, preregistration, managing collaborations, and getting the most out of the Open Science Framework (http://osf.io/) for private and public laboratory operations. Bring your laptop.
 

Using Psychological Science to Write With Clarity and Style

Thursday, May 26 4:00 PM – 5:20 PM

 

Steven A. Pinker, Harvard University

Why is so much writing so bad, and how can we make it better? Do people write badly on purpose, to bamboozle their readers with highfalutin’ gobbledygook? Is the English language being corrupted by texting and social media? Do the kids today even care about good writing? Why should any of us care?

 

I argue that we need to rethink usage advice for the 21st century. Rather than moaning about the decline of the language, carping over pet peeves, or recycling spurious edicts from the rulebooks of a century ago, we can apply insights from the sciences of language and mind to the challenge of crafting clear, coherent, and stylish prose.

 

Don’t blame the Internet, or the kids today; good writing has always been hard. It begins with savoring the good prose of others. Skillful writers must weave their prose into a coherent whole, with one sentence flowing into the next, while negotiating the rules of correct usage and distinguishing the rules that enhance clarity and grace from the myths and superstitions.

 

Uses and Challenges of Mechanical Turk*

Sunday, May 29 8:30 AM – 11:20 AM

 

Matthew Crump, Brooklyn College, The City University of New York
Todd M. Gureckis, New York University

This workshop gives a practical introduction for running behavioral experiments online using Amazon’s Mechanical Turk (AMT). We demonstrate a variety of techniques for programming behavioral experiments in web browsers and for using the AMT system to collect data from the online population of AMT users. The workshop is novice friendly and does not require advanced programming skills. We will 1) introduce basic JAVASCRIPT and HTML programming concepts, 2) give tutorials with working examples on applying those concepts to build a web-based experiment from scratch, and 3) introduce PsiTurk, an online platform for sharing online experiments and running them on AMT.
 

Elegant Multilevel Modeling*

Sunday, May 29 8:30 AM – 12:20 PM

 

Elizabeth Page-Gould, University of Toronto, Canada

This is a practical introduction emphasizing multilevel models as simple extensions of the general linear model, geared toward beginners and long-time practitioners alike. You will be able to specify basic, polynomial, piecewise, multivariate, and Bayesian multilevel models. Data and syntax in R, SAS, SPSS, and BUGS will be provided.
 

Fitting Latent Growth Curves in Longitudinal Research*

Sunday, May 29 8:30 AM – 12:20 PM

 

Jessica A. Logan, The Ohio State University

Latent growth models can measure how skills and abilities change over time. This is an introductory, interactive workshop in which researchers will experience fitting growth curves to their own data using the Mplus program. We will start with research questions and move through data setup, coding, graphing, and output interpretation.
 

Methodological Approaches to Designing Adaptive Interventions in Mobile Health*

Sunday, May 29 8:30 AM – 12:50 PM

 

Susan A. Murphy, University of Michigan
Inbal Nahum-Shani, University of Michigan
Predrag Klasnja, University of Michigan
Daniel Almirall, University of Michigan

A “Just-in-Time Adaptive Intervention” (JITAI) is a mobile health intervention design in which real-time information concerning an individual is used to individualize interventions. We provide an introduction to JITAIs, discuss open scientific questions, and demonstrate how a microrandomized trial can be used to answer these questions.
 

BayesFactor and JASP: A Fresh Way to Do Statistics*

Sunday, May 29 10:00 AM – 12:50 PM

 

Richard D. Morey, Cardiff University, United Kingdom

Bayesian hypothesis testing presents an attractive alternative to p-value hypothesis testing. The most prominent advantages of Bayesian hypothesis testing include (1) the ability to quantify evidence in favor of null hypotheses, (2) the ability to quantify evidence in favor of any alternative hypotheses, and (3) the ability to monitor and update evidence as the data come in. Despite these practical advantages, Bayesian hypothesis testing is still relatively rare. An important impediment to the widespread use of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for almost every experiment: the t-test, analysis of variance, correlation, regression, and contingency tables. Recently, Morey and Rouder released BayesFactor for R (http://bayesfactorpcl.r-forge.r-project.org/), a powerful software for routine Bayesian inference that goes a long way toward solving this problem. In this workshop, Richard Morey introduces JASP, an open-source, user-friendly “point and click” GUI that uses BayesFactor to carry out Bayesian hypothesis tests for standard statistical problems, with no knowledge of R required.

JASP is a collaborative effort with Eric-Jan Wagenmakers at the University of Amsterdam.