Gustavo Amorim

Research Assist Professor

Vanderbilt University Medical Center

United States

Research Interests

Explore related searches

Professors in United States

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Dr. Gustavo Amorim is a Research Assistant Professor at Vanderbilt University Medical Center in the United States. His research focuses on statistical methods for data analysis, including semiparametric likelihood estimation and validation techniques for error-prone data. Recent publications highlight his work on prediction models for adverse drug reactions and patient satisfaction metrics in healthcare settings.

Articles (19)

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Collaborators (6)

Stijn Vansteelandt

BELGIUM

View details

Pamela A Shaw

University of Pennsylvania Perelman School of Medicine

UNITED STATES

View details

Troy Moon

Associate Professor

Vanderbilt University Medical Center

UNITED STATES

View details

Ran Tao

Assistant Professor

Vanderbilt University Medical Center

UNITED STATES

View details

Sarah Lotspeich

Assistant Professor (Tenure Track)

Wake Forest University

UNITED STATES

View details

Rena Patel

The University of Alabama

UNITED STATES

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Gustavo Amorim

Research Interests

Explore related searches

Contact this professor

About

Articles (19)

sleev: An R Package for Semiparametric Likelihood Estimation with Errors in Variables

Ascertainment Conditional Maximum Likelihood for Continuous Outcome Under Two‐Phase Response‐Selective Design

Three‐phase generalized raking and multiple imputation estimators to address error‐prone data

Optimal multiwave validation of secondary use data with outcome and exposure misclassification

Time spent at health facility is a key driver of patient satisfaction, but did not influence retention to HIV care: A serial cross-sectional study in Mozambique

Prediction Models for Adverse Drug Reactions During Tuberculosis Treatment in Brazil

Prediction Models for Adverse Drug Reactions During Tuberculosis Treatment in Brazil

Three-phase generalized raking and multiple imputation estimators to address error-prone data

Semiparametric Estimation of Probabilistic Index Models: Efficiency and Bias

Optimal multiwave validation of secondary use data with outcome and exposure misclassification

Respiratory virus surveillance in hospitalized children less than two-years of age in Kenema, Sierra Leone during the COVID-19 pandemic (October 2020- October 2021).

Pregnancies among women living with HIV using contraceptives and antiretroviral therapy in western Kenya: a retrospective, cohort study

Two‐phase sampling designs for data validation in settings with covariate measurement error and continuous outcome

Determinants of losses in the latent tuberculosis infection cascade of care in Brazil

Efficient odds ratio estimation under two‐phase sampling using error‐prone data from a multi‐national HIV research cohort

Perceived ability to comply with national COVID-19 mitigation strategies and their impact on household finances, food security, and mental well-being of medical and pharmacy students in Liberia

Pre-Treatment Neutrophil Count as a Predictor of Antituberculosis Therapy Outcomes: A Multicenter Prospective Cohort Study

Efficient semiparametric inference for two‐phase studies with outcome and covariate measurement errors

Novel stepwise approach to assess representativeness of a large multicenter observational cohort of tuberculosis patients: The example of RePORT Brazil

Collaborators (6)

Stijn Vansteelandt

Pamela A Shaw

Troy Moon

Ran Tao

Sarah Lotspeich

Rena Patel

Make your next move.