Web Site and R Package for Computing E-values

Epidemiology

Volumn 29, Issue 5, 2018, Pages E45-E47

  Mathur, Maya B ^a,b   Ding, Peng ^a,c   Riddell, Corinne A ^a,d   VanderWeele, Tyler J ^a  

^a HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^b STANFORD UNIVERSITY   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d MCGILL UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ADJUSTMENT; ATTRIBUTABLE RISK; CAUSALITY; CONFOUNDING BIAS; CONFOUNDING VARIABLE; E VALUE; EFFECT SIZE; EVIDENCE BASED PRACTICE; FOLLOW UP; HAZARD RATIO; LETTER; MATHEMATICAL COMPUTING; NULL RESULT; OUTCOME ASSESSMENT; PREVALENCE; PRIORITY JOURNAL; R PACKAGE; REFERENCE VALUE; RISK FACTOR; SENSITIVITY ANALYSIS; STANDARDIZATION; HUMAN; INTERNET; OBSERVATIONAL STUDY; PROCEDURES; STATISTICAL ANALYSIS; STATISTICS;

CAUSALITY; DATA INTERPRETATION, STATISTICAL; HUMANS; INTERNET; OBSERVATIONAL STUDIES AS TOPIC; STATISTICS AS TOPIC;

EID: 85046399523     PISSN: 10443983     EISSN: 15315487     Source Type: Journal    
DOI: 10.1097/EDE.0000000000000864     Document Type: Letter

References (4)

1. VanderWeele TJ, Ding P. Sensitivity analysis in observational research: Introducing the E-value. Ann Intern Med. Am Coll Physicians; 2017; 167:268-274.
2. Ding P, VanderWeele TJ. Sensitivity analysis without assumptions. Epidemiol. Wolters Kluwer Health; 2016; 27:368.
3. Mathur MB, Ding P, VanderWeele TJ. Package 'EValue', version 1.0.0. 2017.
4. Localio AR, Stack CB, Griswold ME. Sensitivity analysis for unmeasured confounding: E-values for observational studies. Ann Intern Med. 2017; 167:285-286.