Propensity Score-Matching Methods for Observational Studies: An Application to Stat 216 Data

dc.contributor.authorTheobold, Allison
dc.date.accessioned2018-10-23T01:28:49Z
dc.date.available2018-10-23T01:28:49Z
dc.date.issued2016-04
dc.description.abstractMany fields of science are faced with the inability to perform randomized experiments, but wish to have the ability to estimate a treatment effect and make causal inference. Propensity score matching is a method that can be used in observational studies to obtain unbiased estimates of the treatment effect. In this paper we consider the theory behind utilizing propensity score matching to obtain these such estimates, as well as explain how to implement propensity score matching in R using the Matching package for data from Montana State University’s Introductory Statistics curriculum.en_US
dc.identifier.urihttps://scholarworks.montana.edu/handle/1/14955
dc.subjectpropensity score matchingen_US
dc.subjecteducationen_US
dc.subjectintroductory statisticsen_US
dc.titlePropensity Score-Matching Methods for Observational Studies: An Application to Stat 216 Dataen_US
dc.typeThesisen_US
mus.data.thumbpage23en_US
mus.identifier.categoryPhysics & Mathematicsen_US
mus.relation.collegeCollege of Letters & Scienceen_US
mus.relation.departmentMathematical Sciences.en_US
mus.relation.universityMontana State University - Bozemanen_US

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