most citedA Semi-Supervised Machine Learning Approach to Detecting Recurrent Metastatic Breast Cancer Cases Using Linked Cancer Registry and Electronic Medical Record Data

58 citations · 94 across the 4 of their papers we have counts for

collaborators

4 papers

stat.AP2022★ 3 cited

Application of Multiple Imputation When Using Propensity Score Methods to Generalize Clinical Trials to Target Populations of Interest

Albee Y. Ling, Maria E. Montez-Rath, Kris Kapphahn +1

When the distribution of treatment effect modifiers differs between the trial sample and target population, inverse probability weighting (IPSW) can be applied to achieve an unbias…

stat.AP2022★ 2 cited

A Critical Review of Methods for Real-World Applications to Generalize or Transport Clinical Trial Findings to Target Populations of Interest

Albee Y. Ling, Maria E. Montez-Rath, Paulo Carita +6

Generalizability and transportability methods have been proposed to address the external validity bias of randomized clinical trials that results from differences in the distributi…

stat.AP2019★ 31 cited

How to apply multiple imputation in propensity score matching with partially observed confounders: a simulation study and practical recommendations

Albee Y. Ling, Maria E. Montez-Rath, Maya B. Mathur +2

Propensity score matching (PSM) has been widely used to mitigate confounding in observational studies, although complications arise when the covariates used to estimate the PS are…

q-bio.QM2019★ 58 cited

A Semi-Supervised Machine Learning Approach to Detecting Recurrent Metastatic Breast Cancer Cases Using Linked Cancer Registry and Electronic Medical Record Data

Albee Y. Ling, Allison W. Kurian, Jennifer L. Caswell-Jin +3

Objectives: Most cancer data sources lack information on metastatic recurrence. Electronic medical records (EMRs) and population-based cancer registries contain complementary infor…