نتایج جستجو برای: causal methods

تعداد نتایج: 1926005  

Journal: :journal of biostatistics and epidemiology 0
kazem mohammad department of epidemiology and biostatistics, school of public health, tehran university of medical sciences, tehran, iran seyed saeed hashemi-nazari safety promotion and injury prevention research center and department of epidemiology, school of public health, shahid beheshti university of medical sciences, tehran, iran nasrin mansournia department of endocrinology, school of medicine, aja university of medical sciences, tehran, iran mohammadali mansournia department of epidemiology and biostatistics, school of public health, tehran university of medical sciences, tehran, iran

conditional  methods  of adjustment  are often used to quantify  the effect  of the exposure on the outcome.  as  a  result,  the  stratums-specific  risk  ratio  estimates  are  reported  in  the  presence  of interaction   between   exposure  and  confounder(s)   in  the  literature,  even  if  the  target  of  the intervention on the exposure is the total population and the interaction itsel...

Journal: :Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery 2022

Causality is a complex concept, which roots its developments across several fields, such as statistics, economics, epidemiology, computer science, and philosophy. In recent years, the study of causal relationships has become crucial part Artificial Intelligence community, causality can be key tool for overcoming some limitations correlation-based Machine Learning systems. research generally div...

2012
Karen Bandeen-Roche Constantine Frangakis Nicholas Ialongo Sherri Rose Michael Rosenblum Daniel Scharfstein Thomas R. Ten Jay Kaufman Susan Murphy Romain Neugebauer Dylan Small Cory Zigler Nikola Andric Donald B. Rubin

In our data-­‐rich world, key medical decisions, ranging from a regulator's decision to curtail a drug to patient-­‐specific treatment choices require optimal consideration of myriad inputs. Statistical/epidemiological methods that can harness real-­‐world medical data in useful ways do exis...

Journal: :International Journal of Epidemiology 2008

2011
Amanda Stevenson

Comparative effectiveness research often uses non-experimental observational data (like hospital discharge records or nationally representative surveys) to draw causal inference about the effectiveness of interventions for health. These ex post inferences require the careful use of specialized statistical methods in order to account for issues like selection bias and unmeasured heterogeneity. T...

Journal: :Journal of Parallel and Distributed Computing 2021

2007
ELIZABETH A. STUART DONALD B. RUBIN

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