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SUMMARY:Propensity Score Analysis Fall 2016
DESCRIPTION:Propensity score analysis is a relatively new and innovati
ve class of statistical methods that has proven useful for evaluating
the effects of treatments or interventions when using nonexperimental
or observational data. Although regression analysis is most often used
to adjust for potentially confounding variables, propensity score ana
lysis is an attractive alternative. Results produced by propensity sco
re methods are typically easier to communicate to lay audiences. And p
ropensity score estimates are often more robust to differences in the
distributions of the confounding variables across the groups being com
pared. This seminar will focus on three closely related but technicall
y distinct propensity score methods:\n\nPropensity score matching and
related methods, including greedy matching, optimal matching, and prop
ensity score weighting using Statapsmatch2, pweights and R optmatch
\nMatching estimators using Stata nnmatch\nPropensity score analysis
with nonparametric regression using Statapsmatch2 and lowess.\n\nThe
examination of these methods will be guided by two conceptual framewo
rks: the Neyman-Rubin counterfactual framework and the Heckman scienti
fic model of causality. The course also covers Rosenbaum’s approache
s of sensitivity analysis to discern bias produced by hidden selection
s. The seminar uses Stata software to demonstrate the implementation o
f propensity score analysis. All syntax files and illustrative data
can be downloaded at the Propensity Score Analysis Support Site.\n\n
For more information visit https://www.datasciencecentral.com/events/p
ropensity-score-analysis-fall-2016
DTSTART;TZID=Pacific/Gambier:20161021T000000
DTEND;TZID=Pacific/Gambier:20161022T235900
CATEGORIES:seminar
LOCATION:Philadelphia
WEBSITE:http://statisticalhorizons.com/seminars/public-seminars/propen
sity-score-analysis
URL:http://statisticalhorizons.com/seminars/public-seminars/propensity
-score-analysis
CONTACT:610-642-1941
ORGANIZER;CN="Statistical Horizons LLC":https://www.datasciencecentral
.com/profile/MaryKiely
ATTACH;FMTTYPE="image/jpeg":
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=ACCEPTED;RSVP=TRUE;CN="Statisti
cal Horizons LLC":https://www.datasciencecentral.com/profile/MaryKiely
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