Time differences and time ratios are often more interpretable estimates of effect than hazard ratios for time-to-event data, especially for common outcomes. We developed a SAS macro for estimating time differences and time ratios between baseline-fixed binary exposure groups based on inverse probability-weighted Kaplan-Meier curves. The macro uses pooled logistic regression to calculate inverse probability of censoring and exposure weights, draws Kaplan-Meier curves based on the weighted data, and estimates the time difference and time ratio at a user-defined survival proportion. The macro also calculates the risk difference and risk ratio at a user-specified time. Confidence intervals are constructed by bootstrap. We provide an example assessing the effect of exclusive breastfeeding during diarrhea on the incidence of subsequent diarrhea in children followed from birth to 3 years in Vellore, India. The SAS macro provided here should facilitate the wider reporting of time differences and time ratios.
%0 Journal Article
%1 Rogawski2016
%A Rogawski, Elizabeth T.
%A Westreich, Daniel J.
%A Kang, Gagandeep
%A Ward, Honorine D.
%A Cole, Stephen R.
%D 2016
%I Lippincott Williams and Wilkins
%J Epidemiology
%K BreastFeeding Child ConfidenceIntervals DanielJWestreich DataInterpretation Diarrhea/epidemiology Diarrhea/prevention&control ElizabethTRogawski EpidemiologicResearchDesign* Extramural Female Follow-UpStudies Humans Incidence India/epidemiology Infant Kaplan-MeierEstimate* MEDLINE Male N.I.H. NCBI NIH NLM NationalCenterforBiotechnologyInformation NationalInstitutesofHealth NationalLibraryofMedicine Newborn OddsRatio PMC5039102 Preschool ProtectiveFactors PubMedAbstract Recurrence ResearchSupport SecondaryPrevention/methods Statistical* StephenRCole Time* doi:10.1097/EDE.0000000000000539 pmid:27465526
%N 6
%P 848-851
%R 10.1097/EDE.0000000000000539
%T Estimating differences and ratios in median times to event
%U https://pubmed.ncbi.nlm.nih.gov/27465526/
%V 27
%X Time differences and time ratios are often more interpretable estimates of effect than hazard ratios for time-to-event data, especially for common outcomes. We developed a SAS macro for estimating time differences and time ratios between baseline-fixed binary exposure groups based on inverse probability-weighted Kaplan-Meier curves. The macro uses pooled logistic regression to calculate inverse probability of censoring and exposure weights, draws Kaplan-Meier curves based on the weighted data, and estimates the time difference and time ratio at a user-defined survival proportion. The macro also calculates the risk difference and risk ratio at a user-specified time. Confidence intervals are constructed by bootstrap. We provide an example assessing the effect of exclusive breastfeeding during diarrhea on the incidence of subsequent diarrhea in children followed from birth to 3 years in Vellore, India. The SAS macro provided here should facilitate the wider reporting of time differences and time ratios.
@article{Rogawski2016,
abstract = {Time differences and time ratios are often more interpretable estimates of effect than hazard ratios for time-to-event data, especially for common outcomes. We developed a SAS macro for estimating time differences and time ratios between baseline-fixed binary exposure groups based on inverse probability-weighted Kaplan-Meier curves. The macro uses pooled logistic regression to calculate inverse probability of censoring and exposure weights, draws Kaplan-Meier curves based on the weighted data, and estimates the time difference and time ratio at a user-defined survival proportion. The macro also calculates the risk difference and risk ratio at a user-specified time. Confidence intervals are constructed by bootstrap. We provide an example assessing the effect of exclusive breastfeeding during diarrhea on the incidence of subsequent diarrhea in children followed from birth to 3 years in Vellore, India. The SAS macro provided here should facilitate the wider reporting of time differences and time ratios.},
added-at = {2023-02-03T11:44:35.000+0100},
author = {Rogawski, Elizabeth T. and Westreich, Daniel J. and Kang, Gagandeep and Ward, Honorine D. and Cole, Stephen R.},
biburl = {https://www.bibsonomy.org/bibtex/241a633ad4a13c26ed315e42f5c020ae6/jepcastel},
doi = {10.1097/EDE.0000000000000539},
interhash = {cfdae6177712931e7b07c8b8d1c7af86},
intrahash = {41a633ad4a13c26ed315e42f5c020ae6},
issn = {15315487},
journal = {Epidemiology},
keywords = {BreastFeeding Child ConfidenceIntervals DanielJWestreich DataInterpretation Diarrhea/epidemiology Diarrhea/prevention&control ElizabethTRogawski EpidemiologicResearchDesign* Extramural Female Follow-UpStudies Humans Incidence India/epidemiology Infant Kaplan-MeierEstimate* MEDLINE Male N.I.H. NCBI NIH NLM NationalCenterforBiotechnologyInformation NationalInstitutesofHealth NationalLibraryofMedicine Newborn OddsRatio PMC5039102 Preschool ProtectiveFactors PubMedAbstract Recurrence ResearchSupport SecondaryPrevention/methods Statistical* StephenRCole Time* doi:10.1097/EDE.0000000000000539 pmid:27465526},
month = {11},
note = {Anàlisi de supervivència; SAS},
number = 6,
pages = {848-851},
pmid = {27465526},
publisher = {Lippincott Williams and Wilkins},
timestamp = {2023-02-03T11:44:35.000+0100},
title = {Estimating differences and ratios in median times to event},
url = {https://pubmed.ncbi.nlm.nih.gov/27465526/},
volume = 27,
year = 2016
}