Dear GEP-ed/ESS Colleagues: Passing on information about a variety of potentially useful 1-hour long introductory workshops organized by
instats.org. Even though these are not specifically focused on GEP, these may be of broad interest to even those who don't do quantitative analysis. On the other hand, for those interested in a deep dive, they are also offering a day-long workshop on a relatively new approach of Necessary Condition Analysis (NCA) -- Please see the information below.
My best wishes,
Prakash
p.s. I will be consulting Michael about whether this kind of (mis)use of this valuable list is permissible : )
Free 1-hour introductions to SPSS, Stata, Mplus, and R
Instats is pleased to announce four new livestreaming 1-hour introductions to SPSS, Stata, Mplus, and R.
Registration is entirely free, and each workshop is designed to provide
participants with a hands-on overview of the software interfaces,
importing and managing data, descriptive statistics, and inferential
statistics including univariate methods (regression/ANOVA) as well as
multivariate methods (factor analysis/path analysis/SEM). Basic plotting
methods will be described along with special features such as
bootstrapping and Bayesian analysis where applicable. To register for
free, you can use the following links -- and please feel free to tell
any colleagues or students who you think might be interested!
Stata seminar (June 7):
R with RStudio seminar (June 21):
https://instats.org/seminar/introduction-to-r-with-rstudio-free-1-h9264
TITLE: Free 1-day seminar on Necessary Condition Analysis (NCA)
For your research, if you've
ever wanted to understand and model causal effects in a rigorous way
that reflects the complexity of the real-world, Instats is offering a
free 1-day workshop:
Introduction to Necessary Condition Analysis (NCA)
running May 10 -- spaces are limited, so sign up soon! NCA understands a
cause as a necessary (but not sufficient) condition, rather than a
probabilistic cause (as in regression analysis). “Necessary” means that a
certain outcome will not occur without a certain level of the
condition. This is independent of the rest of the causal structure. NCA
is rapidly entering a variety of research fields and can be used as a
stand-alone method or in combination with other methods (e.g.,
regression analysis, structural equation modeling, qualitative
comparative analysis).
This free 1-day
seminar is being taught by Jan Dul, who invented NCA and co-authored the
R package for NCA. Registration is entirely free! This seminar is
perfect if, like many of us, you've wanted a way to go beyond simplistic
ANOVA or regression-based approaches to causal effect estimation. The
seminar will introduce you to NCA and then show you how to conduct
analyses and make causal inferences
through a series of worked examples. To register for free, use the
following link -- and please feel free to tell your colleagues and
friends/students!
https://instats.org/seminar/introduction-to-necessary-condition-anal7646
Director
Institute for Statistical and Data Science
instats.org