Straight metalworking fluids and all-cause and cardiovascular mortality analyzed by using g-estimation of an accelerated failure time model with quantitative exposure: methods and interpretations (Q28950714)

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journal article published in 2016

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English	Straight metalworking fluids and all-cause and cardiovascular mortality analyzed by using g-estimation of an accelerated failure time model with quantitative exposure: methods and interpretations	journal article published in 2016

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scholarly article

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15 October 2024

Straight metalworking fluids and all-cause and cardiovascular mortality analyzed by using g-estimation of an accelerated failure time model with quantitative exposure: methods and interpretations (English)

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12 July 2017

National Institute for Occupational Safety and Health

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cardiovascular disease

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29 March 2020

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29 March 2020

3

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Ellen A. Eisen

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DOI.org query endpoint

17 March 2017

author name string

Sally Picciotto

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https://doi.org/10.1093/AJE/KWV232

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Petter L. Ljungman

2

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https://doi.org/10.1093/AJE/KWV232

17 March 2017

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publication date

10 March 2016

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https://doi.org/10.1093/AJE/KWV232

17 March 2017

American Journal of Epidemiology

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https://doi.org/10.1093/AJE/KWV232

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183

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https://doi.org/10.1093/AJE/KWV232

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7

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680-688

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https://doi.org/10.1093/AJE/KWV232

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performing organization

University of California, Berkeley

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University of California - Berkeley

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2 February 2024

on focus list of Wikimedia project

Wikimedia–NIOSH collaboration

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1 reference

25 September 2023

An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure

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Particulate matter air pollution and cardiovascular disease: an update to the scientific statement from the American Heart Association

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Hypothetical exposure limits for oil-based metalworking fluids and cardiovascular mortality in a cohort of autoworkers: structural accelerated failure time models in a public health framework

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Marginal structural models and causal inference in epidemiology

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A comparison of standard methods with g-estimation of accelerated failure-time models to address the healthy-worker survivor effect: application in a cohort of autoworkers exposed to metalworking fluids

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Social disparities in heart disease risk and survivor bias among autoworkers: an examination based on survival models and g-estimation

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Estimation of historical exposures to machining fluids in the automotive industry

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Summary of the findings from the exposure assessments for metalworking fluid mortality and morbidity studies.

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Estimating the effect of cumulative occupational asbestos exposure on time to lung cancer mortality: using structural nested failure-time models to account for healthy-worker survivor bias

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Structural accelerated failure time models for survival analysis in studies with time-varying treatments.

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Estimating the causal effect of smoking cessation in the presence of confounding factors using a rank preserving structural failure time model.

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Causal inference in occupational epidemiology: accounting for the healthy worker effect by using structural nested models

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Healthy worker survivor bias: implications of truncating follow-up at employment termination

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Obstructive coronary atherosclerosis and ischemic heart disease: an elusive link!

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21 January 2018

Concerning the consistency assumption in causal inference.

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21 January 2018

Invited commentary: Estimating population impact in the presence of competing events

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21 January 2018

Compound treatments and transportability of causal inference

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21 January 2018

Identification and estimation of survivor average causal effects

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21 January 2018

Doubly robust estimation and causal inference in longitudinal studies with dropout and truncation by death

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Analysis of occupational asbestos exposure and lung cancer mortality using the g formula

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Occupational exposure to PM2.5 and incidence of ischemic heart disease: longitudinal targeted minimum loss-based estimation

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Identifiers

10.1093/AJE/KWV232

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DOI.org query endpoint

https://doi.org/10.1093/AJE/KWV232

17 March 2017

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