[ICPSR] From ICPSR: Research and Statistical Methods Workshops - starting in May and June

[Linda Detterman]

Take a look at these short workshops!
The 2022 ICPSR Summer Program is just weeks away from officially beginning!
It's hard to believe, but the calendar doesn't lie, and neither do we. Our
first short workshops start May 16 with 2 courses about using R, and
another on better measurement of variables in social science research. Read
on for a highlight of some of our first workshops this year!

See our schedule for 2022 Short Workshops
<https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=a1607d50cd&e=315a5923bb>
for
the full list of courses.
*Methods for Better Measurement of Social Scientific Variables*
May 16-20
Instructor: Adam Enders, University of Louisville
**This course will be held entirely online.**

This course begins with an exploration of the concept of statistical
reliability, including techniques designed to estimate reliability under
different circumstances. We will then consider how to enhance the
reliability of measures vis-à-vis multiple-variable scales. Next, we will
survey several methodologies––such as principal components analysis and
factor analysis––useful for examining the dimensionality of a set of
variables. These methods help bolster both the reliability and validity of
our measurements. Finally, we will learn how to properly execute these
methods in conjunction with one another, what results to report in
scientific books and articles, and other practical aspects of incorporating
better measurement into research projects.
*Introduction to Mixed Methods Research*
May 23-27
Instructor: Shiri Noy, Denison University

Social scientists are often interested in untangling complex social issues,
which require creative and expansive data and methods to address. 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. We will focus on practical
tools and challenges confronted across the stages of mixed methods research.
*Process Tracing in Qualitative and Mixed Methods Research*
June 6-10
Instructor: Derek Beach, Aarhus University

Process tracing is a research method designed to learn how things work in
real-world cases. Increasingly used across the social sciences and in
applied policy evaluation, process tracing involves unpacking causal
processes as they play out within cases and tracing them empirically,
enabling within-case causal inferences about the processes that link causes
and outcomes together. The course will combine pre-class readings with live
sessions aimed at understanding the core elements of Process Tracing as a
distinct case study method. Participants will be encouraged to use their
own research to explore how Process Tracing methods can improve your own
design.
*Network Analysis: Statistical Approaches*
June 6-17
Instructor: John Skvoretz, University of South Florida

The workshop covers advanced statistical methods for analyzing social
network data.  It covers testing hypotheses about network structure (e.g.
reciprocity, transitivity, closure, density, clustering, path lengths,
geometrically weighted graph metrics), models for the formation of ties
based on attributes (e.g. homophily) and on structural effects (e.g.,
closure in triads), and models for network effects on individual attributes
(social influence or contagion models).  Topics include: random graph
distributions, statistical analysis of local structural regularities in
dyads and triads, assessment of hypotheses about graph-level indices,
biased net models for realized ties and for complete networks, peer
influence models and other regression based models for network data,
exponential random graph models, and stochastic actor-oriented models.
Each session divides into lecture/discussion of methods and a lab using
those methods. This workshop assumes that participants have already taken a
first course in network analysis.
Full Short Workshop Schedule
<https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=246d0b28dd&e=315a5923bb>

*Stay up-to-date with the Summer Program!*
You can keep up with the program on social media (Twitter,
<https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=0e1d28d945&e=315a5923bb>
 Facebook
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, Instagram
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or sign up for our email list. Or both!
Subscribe to the Summer Program email list
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------------------
Scott Campbell
ICPSR Summer Program Communications & Video Services Coordinator
Follow the Summer Program on social media!
<https://www.facebook.com/ICPSRSummerProgram/>
<https://twitter.com/ICPSRSummer>
<https://www.instagram.com/icpsrsummer/>
<https://www.youtube.com/channel/UCgQWgr9Np3SKx54T_0hbo-Q>
https://www.icpsr.umich.edu/icpsrweb/sumprog/
he/him
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