Literature DB >> 33716397

Automated analyses: Because we can, does it mean we should?

Susan M Shortreed1, Erica E M Moodie1.   

Abstract

Entities:  

Year:  2020        PMID： 33716397      PMCID： PMC7946328          DOI： 10.1214/20-sts773

Source DB:  PubMed          Journal:  Stat Sci        ISSN： 0883-4237            Impact factor:   2.901


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  15 in total

1.  Invited commentary: variable selection versus shrinkage in the control of multiple confounders.

Authors:  Sander Greenland
Journal:  Am J Epidemiol       Date:  2008-01-27       Impact factor: 4.897

2.  Registration of observational studies.

Authors:  Elizabeth Loder; Trish Groves; Domhnall Macauley
Journal:  BMJ       Date:  2010-02-18

3.  Robust inference on the average treatment effect using the outcome highly adaptive lasso.

Authors:  Cheng Ju; David Benkeser; Mark J van der Laan
Journal:  Biometrics       Date:  2019-10-30       Impact factor: 2.571

4.  The Balance Super Learner: A robust adaptation of the Super Learner to improve estimation of the average treatment effect in the treated based on propensity score matching.

Authors:  Romain Pirracchio; Marco Carone
Journal:  Stat Methods Med Res       Date:  2016-12-15       Impact factor: 3.021

5.  A note on overadjustment in inverse probability weighted estimation.

Authors:  Andrea Rotnitzky; Lingling Li; Xiaochun Li
Journal:  Biometrika       Date:  2010-07-31       Impact factor: 2.445

6.  Big data. The parable of Google Flu: traps in big data analysis.

Authors:  David Lazer; Ryan Kennedy; Gary King; Alessandro Vespignani
Journal:  Science       Date:  2014-03-14       Impact factor: 47.728

7.  Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available.

Authors:  Miguel A Hernán; James M Robins
Journal:  Am J Epidemiol       Date:  2016-03-18       Impact factor: 4.897

8.  Outcome-adaptive lasso: Variable selection for causal inference.

Authors:  Susan M Shortreed; Ashkan Ertefaie
Journal:  Biometrics       Date:  2017-03-08       Impact factor: 2.571

9.  Dissecting racial bias in an algorithm used to manage the health of populations.

Authors:  Ziad Obermeyer; Brian Powers; Christine Vogeli; Sendhil Mullainathan
Journal:  Science       Date:  2019-10-25       Impact factor: 47.728

10.  Improving reproducibility by using high-throughput observational studies with empirical calibration.

Authors:  Martijn J Schuemie; Patrick B Ryan; George Hripcsak; David Madigan; Marc A Suchard
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2018-09-13       Impact factor: 4.226
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