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Frontiers in Education, 2022 Workplace discrimination continues to at least be perceived as a problem by faculty and staff in higher education. The current study extends the academic literature in this area by exploring the possibility of gender discrimination in the wages of ...
Steven B. Caudill +3 more
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On inverse probability-weighted estimators in the presence of interference [PDF]
Biometrika, 2016 We consider inference about the causal effect of a treatment or exposure in the presence of interference, i.e., when one individual’s treatment affects the outcome of another individual. In the observational setting where the treatment assignment mechanism is not known, inverse probability-weighted estimators have been proposed when individuals can be ...
Liu, L. +2 more
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A note on overadjustment in inverse probability weighted estimation [PDF]
Biometrika, 2010 Standardized means, commonly used in observational studies in epidemiology to adjust for potential confounders, are equal to inverse probability weighted means with inverse weights equal to the empirical propensity scores. More refined standardization corresponds with empirical propensity scores computed under more flexible models.
Andrea Rotnitzky +2 more
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Demographics after inverse probability weighting.
, 2022 Demographics after inverse probability weighting.
Kiyuk Chang (3620258) +18 more
core +1 more source
Understanding Marginal Structural Models for Time-Varying Exposures: Pitfalls and Tips
Journal of Epidemiology, 2020 Epidemiologists are increasingly encountering complex longitudinal data, in which exposures and their confounders vary during follow-up. When a prior exposure affects the confounders of the subsequent exposures, estimating the effects of the time-varying
Tomohiro Shinozaki, Etsuji Suzuki
doaj +1 more source
Inverse Probability Weights for the Analysis of Polytomous Outcomes [PDF]
American Journal of Epidemiology, 2018 Polytomous outcomes are common in epidemiologic studies. Analyses based on multinomial models employ a likelihood that utilizes the data observed in all outcome categories simultaneously and permits inferences regarding associations across outcome categories.
David B, Richardson +5 more
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BMC Medical Informatics and Decision Making, 2020 Background and objectives Height and weight data from electronic health records are increasingly being used to estimate the prevalence of childhood obesity.
Carmen Sayon-Orea +9 more
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Differences in Abdominal Body Composition According to Glycemic Status: An Inverse Probability Treatment Weighting Analysis [PDF]
Endocrinology and Metabolism, 2021 Background Several studies have reported that abdominal fat and muscle changes occur in diabetic patients. However, there are few studies about such changes among prediabetic patients.
Seungbong Han +6 more
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Accounting for nonmonotone missing data using inverse probability weighting. [PDF]
Stat Med, 2023 Inverse probability weighting can be used to correct for missing data. New estimators for the weights in the nonmonotone setting were introduced in 2018. These estimators are the unconstrained maximum likelihood estimator (UMLE) and the constrained Bayesian estimator (CBE), an alternative if UMLE fails to converge.
Ross RK +5 more
europepmc +4 more sources
Risks of outcomes among immunocompromised patients after inverse probability of treatment weighting.
, 2021 Risks of outcomes among immunocompromised patients after inverse probability of treatment weighting.
Sun-Young Jung (295962) +4 more
core +1 more source