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30th APS Annual Convention

Using Advanced Statistical Methods with Large Longitudinal Data Sets to Gain Insight Into the Needs of Vulnerable Populations

Sunday, May 27, 2018 · San Francisco, CA

Oral · Methodology

Increasingly, advanced statistical methods are being used by health/mental health scientists to test hypotheses about naturally occurring behavior change. Discussion will focus on the application of conditional/logistic regression, growth path, and structural equation models to large longitudinal data-sets. Insights into adolescent suicide, bilingualism, health-related disparities are discussed.

Chairs & Discussants

  • Alexander KhislavskyChair
    University of California, Merced
  • Jeffrey GilgerCoChair
    University of California, Merced

Presentations

  1. Predicting Adolescent Emergency Department Visits for Self-Injury: Case-Control and Cohort Analyses Using Statewide Data from CaliforniaSidra Goldman-Mellor, Kevin Kwan, Boyajian Jonathan, Magdalena Cerda
  2. Evidence of a ‘Bilingual Advantage’ in Attention and Executive Function: Analyzing a Nationally Representative Elementary School Sample, Using Growth Curve ModelsAnabel Castillo, Jeffrey Gilger, Alexander Khislavsky, Meghan Altman
  3. Health-Related Issues in Latina Youth: Racial/Ethnic, Gender, and Generational Status DifferencesGeraldy Martin-Gutierrez, Jan Wallander, Anna Song
  4. Using Structural Equation Modeling Path Analysis to Explore Associations between Parental SES and Children’s Health-Related Quality of LifeKay Kim, Jan Wallander, Melissa Peskin, Paula Cuccaro