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Second-best probability weighting [PDF]
, 2023 Non-linear probability weighting is an integral part of descriptive theories of choice under risk such as prospect theory. But why do these objective errors in information processing exist?
Netzer, Nick; https://orcid.org/ +2 more
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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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Journal of Biostatistics and Epidemiology, 2020 Introduction: Missing values are frequently seen in data sets of research studiesespecially in medical studies.Therefore, it is essential that the data, especially in medical research should evaluate in terms of the structure of missingness.This study ...
Freshteh Osmani, Ebrahim Hajizadeh
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Application of inverse probability weights in survival analysis [PDF]
Journal of Nuclear Cardiology, 2015 Suppose that a researcher is interested in comparing two ‘‘treatments’’—A and B—and how the treatment affects an outcome of interest. The ideal study design would be to conduct a randomized trial where treatment assignment is randomly assigned. The random treatment assignment aims to make the subjects between the two treatments similar, i.e., it aims ...
Guoqiao, Wang, Inmaculada, Aban
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Inverse probability weighting for clustered nonresponse [PDF]
Biometrika, 2011 Correlated nonresponse within clusters arises in certain survey settings. It is often represented by a random effects model and assumed to be cluster-specific nonignorable, in the sense that survey and nonresponse outcomes are conditionally independent given cluster-level random effects.
Chris J. Skinner, Julia D'Arrigo
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An introduction to inverse probability of treatment weighting in observational research [PDF]
Clinical Kidney Journal, 2021 ABSTRACTIn this article we introduce the concept of inverse probability of treatment weighting (IPTW) and describe how this method can be applied to adjust for measured confounding in observational research, illustrated by a clinical example from nephrology. IPTW involves two main steps. First, the probability—or propensity—of being exposed to the risk
Chesnaye, Nicholas C +6 more
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Demographics after inverse probability weighting.
, 2022 Demographics after inverse probability weighting.
Kiyuk Chang (3620258) +18 more
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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
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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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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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