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Comparison of Methods for Handling Covariate Missingness in Propensity Score Estimation with a Binary Exposure

Research Square(2020)10.21203/rs.2.18726/v2Source: DataRank Database

Comparison of Methods for Handling Covariate Missingness in Propensity Score Estimation with a Binary Exposure is a research paper published in Research Square (2020). On theSindex it has a DataRank of 0. It has been cited 1 time.

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Authors (3)

Jiangxiu Zhou,Xizhen Cai ORCID,Donna L. Coffman ORCID

Live enrichment

PubMed:42529674 OpenAlex:https://openalex.org/W4255317692

National Institutes of Health

Grant: 1K01ES025437-01

Novel Methods to Identify Momentary Risk States for Stress & Physical Inactivity

National Institutes of Health

Grant: 5R01DA045049-02

Improving Causal Inference Tools for Addiction Researchers

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repositoryhttps://www.researchsquare.com/article/rs-9344/v2.pdf

publisherhttps://www.researchsquare.com/article/rs-9344/v2

publisherhttps://www.researchsquare.com/article/rs-9344/v2.html

repositoryhttps://doi.org/10.21203/rs.2.18726/v2

Fields of Study

Statistical Methods and InferenceStatistical Methods and Bayesian InferenceAdvanced Causal Inference Techniques01 natural sciences03 medical and health sciences0302 clinical medicine0101 mathematics

Keywords

CovariateMissing dataPropensity score matchingStatisticsEstimationBinary numberMathematicsEconometricsEconomicsMedicine (General)Models, StatisticalGeneralized boosted modelsCausalityPropensity scoresR5-920BiasResearch DesignData Interpretation, StatisticalHumansComputer SimulationPropensity ScoreCausal inferenceResearch Articlenavigationoperative efficiencyspine surgeryultrasonography

Sustainable Development Goals

SDG 3: 3. Good health