[ICPSR] Upcoming workshops in Bayesian and Dynamic Panel Models

[Linda Detterman]

Please forward this email to students, faculty, and researchers who would
benefit from ICPSR courses!
View this email in your browser
<https://mailchi.mp/icpsr/upcoming-workshops-in-bayesian-and-dynamic-panel-models-3967417?e=17afda8ecf>
*Less than 100 days left of the 2020 Summer Program! *
We're almost through the second week of the program! Considering that just
two months ago we announced our move to online-only instruction, we
couldn't be happier with the way our workshops have run so far. In case you
missed our announcement last week, we have a lot of information about how
online courses function with recording, platform, and time zones posted on
our homepage
<https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=9a3764e1c1&e=17afda8ecf>.
Today though we're looking into the future a bit with these upcoming
workshops.

Dynamical Systems Analysis
<https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=ba4a5bccd2&e=17afda8ecf>
(June 15-18)
*Instructors: Brian Baucom, University of Utah; Jonathan Butner, University
of Utah*

Dynamic systems models provide a unique lens for studying change over time;
the focus in these models is on patterns of fluctuations about the mean,
the stability of these patterns, and how these patterns change under
different conditions. Research focused on how individuals, families,
groups, and communities grow and change over time is increasingly
recognizing the vast potential of dynamic systems models for advancing
understanding of complex temporal phenomena.

This four day short course includes a balance of didactic instruction in
background material and guided practice in estimating and interpreting
models.


Bayesian Multilevel Models
<https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=22b837662b&e=17afda8ecf>
(June 15-19)
*Instructor: Ryan Bakker, University of Essex*

Bayesian methods allow for an extremely flexible approach for estimating
hierarchical models with a variety different types of dependent variables.
The Bayesian approach simplifies several of the assumptions of the
classical techniques for MLMS and directly estimates a variety of
quantities of interest that require post-estimation methods in the
non-Bayesian framework. Topics covered will be the hierarchical linear
model, as well as a models with limited dependent variables, summarizing
results, in and out of sample predictions, and measures of model fit. No
prior knowledge of Bayesian modeling is required, but will be beneficial.

Advanced Topics in Dynamic Panel Models
<https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=c4b536e155&e=17afda8ecf>
(July
20-22)
*Instructors: Mark Pickup, Simon Fraser University; Andrew Philips,
University of Colorado at Boulder*

Data collected over both units (e.g., individuals, states, countries) and
time (e.g., days, months, years) — known as time series cross-sectional
data or panel data — are common in the social sciences. By gaining leverage
both across units and over time, these data help us answer important
questions that would be difficult if we only looked at a single point in
time (e.g., cross section) or single unit (e.g., time series): the
relationship between growth and democracy, whether or not the resource
curse exists, or how economic perceptions shape support for the government.
Despite these advantages, panel data often show types of heterogeneity and
dynamics that make standard regression approaches inappropriate.

This course is designed to survey some advanced topics in panel data. After
a review of panel data fundamentals, we will cover topics such as panel
unit root and cointegration tests, panel error correction models, and
approaches to modeling dynamics in panel data with a small T.
*REMINDER: *All 2020 Summer Program courses are being offered virtually!
View all 2020 courses
<https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=504d30c4ef&e=17afda8ecf>

*Registration now open, reduced fees!*
To register for these or any of our courses visit our Registration page
<https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=59ee2aa6a7&e=17afda8ecf>
to
get started. Also on that page is our new fee structure, reduced to reflect
our move online for 2020.
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*Copyright © 2020 ICPSR Summer Program in Quantitative Methods of Social
Research, All rights reserved.*
You are receiving this email because you are a participant, TA, instructor,
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*Our mailing address is:*
ICPSR Summer Program in Quantitative Methods of Social Research
P.O. Box 1248
Ann Arbor, MI 48106-1248


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