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Rebecca Loeb

Biographic Data

ID6067089
NAMERebecca Loeb
GIVEN NAMESRebecca
FAMILY NAMELoeb
SIGNATURELOEB R
AFFILIATIONSMemorial Sloan Kettering Cancer Center
VERIFIEDNo
TOTAL WORKS3
TOTAL CITATIONS1
AUTHOR COUNT3
EDITOR COUNT0
FIRST PUBLICATION YEAR2015
LATEST PUBLICATION YEAR2018
H-INDEX1
  • Bayesian Latent Class Analysis Tutorial

    Yuelin Li, Jennifer Lord-Bessen et al.•ARTICLE•Multivariate Behavioral Research•2018

    This article is a how-to guide on Bayesian computation using Gibbs sampling, demonstrated in the context of Latent Class Analysis (LCA). It is written for students in quantitative psychology or related fields who have a working knowledge of Bayes Theorem and conditional probability and have experience in writing computer programs in the statistical language R . The overall goals are to provide an accessible and self-contained tutorial, along with…

  • Step On It! Workplace Cardiovascular Risk Assessment of New York City Yellow Taxi Drivers

    Open Access•Francesca Gany, Sehrish Bari et al.•ARTICLE•Journal of Immigrant and Minority…•2015

  • Step On It! Impact of a Workplace New York City Taxi Driver Health Intervention to Increase Necessary Health Care Access

    Francesca Gany, Sehrish Bari et al.•ARTICLE•American Journal of Public Health•2015•Cited by: 1•References: 29

    Objectives. We describe the impact of the Step On It! intervention to link taxi drivers, particularly South Asians, to health insurance enrollment and navigate them into care when necessary. Methods. Step On It! was a worksite initiative held for 5 consecutive days from September 28 to October 2, 2011, at John F. Kennedy International Airport in New York City. Data collected included sociodemographics, employment, health care access and use, heig…

  • Step On It! Impact of a Workplace New York City Taxi Driver Health Intervention to Increase Necessary Health Care Access

    Francesca Gany, Sehrish Bari et al.•ARTICLE•American Journal of Public Health•2015•Cited by: 1•References: 29

    Objectives. We describe the impact of the Step On It! intervention to link taxi drivers, particularly South Asians, to health insurance enrollment and navigate them into care when necessary. Methods. Step On It! was a worksite initiative held for 5 consecutive days from September 28 to October 2, 2011, at John F. Kennedy International Airport in New York City. Data collected included sociodemographics, employment, health care access and use, heig…

  • Step On It! Workplace Cardiovascular Risk Assessment of New York City Yellow Taxi Drivers

    Open Access•Francesca Gany, Sehrish Bari et al.•ARTICLE•Journal of Immigrant and Minority…•2015

  • Step On It! Impact of a Workplace New York City Taxi Driver Health Intervention to Increase Necessary Health Care Access

    Francesca Gany, Sehrish Bari et al.•ARTICLE•American Journal of Public Health•2015•Cited by: 1•References: 29

    Objectives. We describe the impact of the Step On It! intervention to link taxi drivers, particularly South Asians, to health insurance enrollment and navigate them into care when necessary. Methods. Step On It! was a worksite initiative held for 5 consecutive days from September 28 to October 2, 2011, at John F. Kennedy International Airport in New York City. Data collected included sociodemographics, employment, health care access and use, heig…

  • Bayesian Latent Class Analysis Tutorial

    Yuelin Li, Jennifer Lord-Bessen et al.•ARTICLE•Multivariate Behavioral Research•2018

    This article is a how-to guide on Bayesian computation using Gibbs sampling, demonstrated in the context of Latent Class Analysis (LCA). It is written for students in quantitative psychology or related fields who have a working knowledge of Bayes Theorem and conditional probability and have experience in writing computer programs in the statistical language R . The overall goals are to provide an accessible and self-contained tutorial, along with…

Environmental health (2 works) · Gerontology (2 works) · Medicine (2 works) · Sleep and Work-Related Fatigue (2 works) · Advanced Statistical Methods and Models (1 works) · Air Quality and Health Impacts (1 works) · Algorithm (1 works) · Approximate Bayesian Computation (1 works) · Artificial Intelligence (1 works) · Artificial Intelligence (1 works)

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