[ICPSR] Week 2 of Short Workshops with the ICPSR Summer Program

[Linda Detterman]

*Causal Inference, Group-based Trajectory Modeling, and more!*
Today we have six more short workshops to feature, all starting the week of
May 18. If you are reading perhaps tomorrow or even later, don't worry.
This email is not time sensitive nor self-destructive. As part of a data
archive we are strongly against any Mission: Impossible-style archiving
protocols. See what we have to offer for the second week of our 2020
program:

Introduction to Causal Inference
<https://www.icpsr.umich.edu/icpsrweb/sumprog/courses/0285> (May 18-22)
*Instructor: Stephen Jesse, University of Texas*

This course will cover methods for making causal claims with observational,
rather than experimental, data. It will cover the potential outcomes
framework for thinking about causality and will introduce students to
several approaches for estimating causal effects when true randomized
experiments are not possible. The topics covered will include regression,
matching, instrumental variables, differences in differences, and
regression discontinuity designs. Students will also learn how to think
about potential problems with causal claims including selection bias,
controlling for post treatment variables, and other issues.

Linear Regression Analysis in the Social Sciences
<https://www.icpsr.umich.edu/icpsrweb/sumprog/courses/0253> (May 18-22)
*Instructors: Patrick Shea, University of Houston; Sunny Wong, University
of Houston*

The course will be centered around several main topics covering the basic
analysis of ordinary least squares (OLS), the technique of estimating
bivariate and multivariate regression models, the overall fitness of a
regression equation, and the hypothesis and diagnostic testings, and more.
This course takes the "learning by doing" approach by discussing the major
themes in regression analysis with detailed examples, which show how the
subject works in practice using Stata.

Network Analysis
<https://www.icpsr.umich.edu/icpsrweb/sumprog/courses/0233> (May
18-22)
*Instructor: Jimi Adams, University Colorado Denver*

This course will lay the groundwork behind social network analysis (SNA)
from conceptual, mathematical, empirical and computational perspectives.
This approach will draw from the rich multidisciplinary history that has
shaped the field's development - incorporating perspectives from sociology
to physics, math to public health.

SNA differs from other analytic perspectives in ways that require unique
strategies for data collection, storage, descriptive and statistical
analysis. The course will address each of these by sampling from a range of
the most commonly used analytic concepts, and demonstrate their empirical
applications, and computation (primarily in R).


N <https://www.icpsr.umich.edu/icpsrweb/sumprog/courses/0284>etwork
Analysis: Statistical Approaches
<https://www.icpsr.umich.edu/icpsrweb/sumprog/courses/0176> (May 18-22)
*Instructor: John Skvoretz, University of South Florida*

This workshop covers advanced statistical methods for analyzing social
network data, focusing on testing hypotheses about network structure (e.g.
reciprocity, transitivity, and closure), the formation of ties based on
attributes (e.g. homophily), and network effects on individual attributes
(social influence or contagion models). Topics include random graph
distributions, statistical models for local structure (dyads and triads),
biased net models for complete networks and for aggregated tie count data,
dyadic independence models, autocorrelation models, exponential random
graph models, and stochastic models for dynamic network analysis.

Introduction to Mixed Methods Research
<https://www.icpsr.umich.edu/icpsrweb/sumprog/courses/0276> (May 20-22)
*Instructor: Shiri Noy, Denison University*

The goal of the course is to introduce students to conceptual and practical
frameworks and considerations in developing, designing, implementing,
executing, analyzing, presenting, and writing up mixed methods research.
Mixed methods research typically refers to research design and
implementation that combines qualitative and quantitative data collection
and/or analysis techniques. In the course we will interrogate the utility
of mixed methods research in light of the limitations of any specific
methodological tool and approach, and review the theory and practice of
mixed methods research in the social sciences.

Group-based Trajectory Modeling for the Medical and Social Sciences
<https://www.icpsr.umich.edu/icpsrweb/sumprog/courses/0032> (May 20-22)
*Instructors: Daniel Nagin, Carnegie Mellon University; Thomas Loughran,
Pennsylvania State University*

A developmental trajectory describes the course of a behavior over age or
time. This two-and-a-half-day workshop aims to provide participants with
the training to apply a group-based method for analyzing developmental
trajectories. Participants should have a statistical background of matrix
algebra and multiple regression. This workshop is targeted at researchers
from the social and behavioral sciences and medicine who investigate
developmental processes.

*REMINDER: *All 2020 Summer Program courses are being offered virtually!

To register for these or any of our courses, visit our Registration page
<https://www.icpsr.umich.edu/icpsrweb/content/sumprog/registration.html>to
get started! Or you can view all 2020 courses on our Schedule page
<https://www.icpsr.umich.edu/icpsrweb/content/sumprog/schedule.html>.
*--*

*ICPSR Summer Program*
http://www.icpsr.umich.edu/sumprog/
P.O. Box 1248
Ann Arbor, Michigan 48106
734-763-7400

Follow the Summer Program on Twitter <https://twitter.com/ICPSRSummer>,
Facebook <https://www.facebook.com/ICPSRSummerProgram>, Instagram
<https://www.instagram.com/icpsrsummer/>, and YouTube
<https://www.youtube.com/channel/UCgQWgr9Np3SKx54T_0hbo-Q>
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