Dear all,

Hope this note finds you well. This is a gentle reminder that registration
for the StarFlame Summer Institute on Advanced Methods Training will close
in about two weeks. (Please let us know if you need more time to submit the
registration.) Short descriptions of selected courses are shown below.
Tuition is minimal and there is also a discount for economic hardship. For
more details, please visit:

*https://www.starflame.org/training <https://www.starflame.org/training>*

We also invite you to join our mailing list (
https://forms.gle/WrwW8Cg4iGvYj5kL8) to stay updated with new course
offerings, scholarship opportunities, and other events. Please feel free to
share the information with others. Many thanks!



*1.    **Causal Inference, July 27-30, 2022 (11am-1:30pm, US EST)*

https://www.starflame.org/training/causal-inference

*Correlation is not causation. Counterfactual causal inference is one of
the most revolutionary inventions in statistics and social science research
methods. Based on the potential outcomes framework, this course presents
the state-of-art of causal inference methods. Selected topics include the
concept of potential outcomes, randomized experiments, matching, propensity
score methods, sensitivity analysis, instrumental variables, regression
discontinuity, difference-in-difference, synthetic control, marginal
structural models, nonbinary treatment, mediation, and interference.
Examples and code will be provided. Knowledge of R (or Stata) and logistic
regression is required.*



*2.    **Structural Equation Models, August 1-4, 2022 (11am-1:30pm, US EST)*

https://www.starflame.org/training/SEM

*Widely used in social and behavioral sciences, structural equation models
(SEM) provide a highly valuable framework for integrating measurement and
mediation analysis into statistical modeling. An SEM allows linking latent
(or unobserved) variables to observed ones in order to address measurement
error. It also permits the specification of multiple dependent variables
simultaneously and an assessment of mediation based on the decomposition of
total effects into direct and indirect effects. This course emphasizes the
intuition behind SEMs and their applications. Examples, exercises, and code
(R or Stata) will be provided. Knowledge of R (or Stata) and linear
regression is required.*



*3.    **Bayesian Analysis, August 11-14, 2022 (11am-1:30pm, US EST)*

https://www.starflame.org/training/bayesian-analysis

*Bayesian analysis is revolutionary in that it can estimate complex models
with no analytical solutions and also incorporate prior knowledge. This
course introduces Bayesian analysis in a conceptually accessible way, with
a focus on application and interpretation. Selected topics include the
history of Bayesian analysis, the Bayes's theorem, the basics of likelihood
theory, the Markov chain Monte Carlo methods, applications of the Bayesian
methods for estimating generalized linear models and multilevel regression
models, and post-estimation analysis (model diagnostics and comparisons).
Examples and R code will be provided. Knowledge of R and linear regression
is required.*



*4.    **Network Analysis, August 15-18, 2022 (11am-1:30pm, US EST)*

https://www.starflame.org/training/network-analysis

*Network analysis shifts the research focus from individual units to their
connections and so brings both theoretical and methodological innovations.
Interest in network analysis has EXPLODED recently, due to new advances in
statistical modeling and the rapid growth of network data. This course
covers the major methods to collect and analyze network data. Selected
topics include basic network analysis (centrality, positions, and
clustering), the exponential random graph model for modeling network
formation, causal analysis of network effects, the stochastic
actor**‐**oriented
model for dynamic network analysis, and meta network analysis for combining
and comparing estimates from multiple random graph models. Case studies and
R code will be provided. Knowledge of R and logistic regression is
required.*



*StarFlame (**https://www.starflame.org/* <https://www.starflame.org/>*)
aims to provide the most cutting-edge, efficient, and affordable training
in advanced research methods within 10 hours*.

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               Political Methodology E-Mail List
   Editors:  Dominique Lockett and Gechun Lin
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