Introduction to Family-based Analyses

Learn essential techniques for analyzing publicly available sibling, twin, family, and/or cousin data in this hands-on beginner course. Useful for researchers in the social, behavioral, and medical sciences. Unlock a whole new world of inferential power by fully capitalizing on your family-based samples!

Instructors:
S. Alexandra Burt, PhD (Michigan State University)

Workshop Dates and Times:
Thursday, July 18, 2024, 10:00am to 4:00pm ET
Friday, July 19, 2024, 10:00am to 4:00pm ET

Workshop Format:
Two-Day Synchronous Online Workshop

Family-based data can dramatically enhance the inferential power of non-experimental research projects within the social, behavioral, and medical sciences. These data can make it possible, for example, to rule-out family confounds in your conclusions and to determine if a given association between a predictor and an outcome is indeed environmental in origin. Perhaps not surprisingly then, family members have been intentionally embedded in most large-scale publicly available databases (e.g., ABCD, AdHealth, among others), in large scale pedigree data in the US and elsewhere, and even in the smaller family-based studies commonly collected in the field of child development.

Critically, however, very few applied researchers outside of particular sub-specialty areas have leveraged these inferential advantages. The main hurdles have been two-fold. First, applied researchers often assume that family-based methods are useful only for analyzing twin data, when in fact they are useful for nearly all family structures: full siblings, half siblings, parent-child, stepparent-child, first cousins, second cousins, and many others. Second, although both intuitive and extraordinarily useful once learned, neither the key concepts nor the specific analyses necessary to capitalize on the advantages of family-based data are taught in most applied graduate programs. This two-day workshop is designed to provide both the conceptual and statistical knowledge teach needed to conduct the most common and useful of family-based analyses.

The introductory workshop assumes that attendees have no prior knowledge of or experience with family-based models. The knowledge gained in this beginner workshop will be invaluable for the Advanced Analyses in Behavioral Genetics workshop, which focuses on more advanced structural equation models, including multivariate and genotype-environment interaction (GxE) models.

What you’ll learn

  • Finding family data

    • Identifying specific samples

    • Determining which samples would be useful for your questions

    • Designing a family-level study

  • Conceptual underpinnings of family-based data

    • Contributions of genes and environments

    • Sources of kinship differences

    • Standard etiologic inferences

    • Addressing family-level confounds

  • Within-family models

    • Multi-level modeling

    • Sibling/twin difference analyses

    • Co-sibling/twin control analyses

  • Data preparation for each analysis

  • Interpretation of family-based analyses

Syllabus

  • The principles and concepts underlying family-based methods and models

  • Sources of similarities and differences across different kinships

  • Practical demonstrations of a series of progressively more sophisticated models (i.e., MLM approach, kinship differences approach, co-twin/sibling control approach)

    • How to choose the correct family-based analysis for your question

    • Conducting appropriate data preparation and management for a given analysis

    • How to troubleshoot while running analyses

    • How to interpret the results

  • To solidify their learning, students will engage in significant hands-on learning, applying each method to existing data. These learning activities will include preparing the data for analysis, running the analyses, and interpreting the results

  • Office hours with the instructor will be offered at the end of the course for students to troubleshoot analyses in their own data

Registration Options

Introduction to Family-based Analyses

  • Professional
  • $599
  • Baseline Price for Faculty,
    Staff, and Other Professionals
  • Click Register Below
  • Trainee
  • $599 $399
  • 33% Discount for
    Students and Postdocs
  • Use code "TRAINEE" at Checkout

Combo 1: Introduction to Family-based Analyses + Advanced Biometric Analysis in Behavioral Genetics

  • Professional
  • $1423 $1139
  • Baseline Price for Faculty,
    Staff, and Other Professionals
  • 20% Combination Discount
  • Click Register Below
  • Trainee
  • $1139 $759
  • 33% Discount for
    Students and Postdocs
  • 20% Combination Discount
  • Use code "TRAINEE" at Checkout

 FAQs

  • This introductory workshop was custom built for researchers in the social, behavioral, and medical sciences who work with data but may not have received much (if any) formal education in family-based and behavioral genetic analyses. It is designed to be highly accessible to researchers in child development, medicine, clinical, social, and personality psychology, social work, among many others. This workshop is appropriate for faculty, staff, and students at both the graduate and advanced undergraduate levels.

  • Beginner

  • This workshop assumes that attendees have no prior knowledge of or experience with behavioral genetics or family-based models. It does, however, assume that learners have basic computing skills such as the ability to download and manage (e.g., copy and paste) files, install and run software, and use a web browser to access workshop materials. Participants are also expected to have a working knowledge of regression, as well as SPSS.

  • Demonstrations and analyses will be conducted in SPSS, a very common statistical software in applied fields. If students would rather conduct their analyses in Mplus or R, we may be able to accommodate that as well.

  • Registered learners will gain access to the Zoom link and passcode to attend the synchronous workshop, as well as video recordings of the lectures, downloadable slideshows, and example data files.