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KMSENSPEC: Stata module to estimate sensitivity, specificity and predictive values from Kaplan-Meier curves

Author

Listed:
  • Roger Newson

    (King's College London)

Programming Language

Abstract

kmsenspec is intended for use in a survival time dataset set up by stset. It inputs a binary variable indicating a positive test result, and estimates positive and negative predictive values from Kaplan-Meier survival probabilities at a time specified by the user in positive and negative observations, and then estimates the sensitivity and specificity of the test using the Bayes theorem, with delta-Greenwood variances estimated from the Greenwood standard errors of the positive and negative predictive values. The estimation results are estimates of the sensitivity, specificity, negative predictive power, and positive predictive power, with a covariance matrix for the untransformed estimates. Alternatively, kmsenspec can be used with the SSC packages parmest and esetran to compute delta-Greenwood confidence intervals using a variety of Normalizing transforms. The kmsenspec package uses the SSC package kmest, which must be installed in order for kmsenspec to work.

Suggested Citation

  • Roger Newson, 2025. "KMSENSPEC: Stata module to estimate sensitivity, specificity and predictive values from Kaplan-Meier curves," Statistical Software Components S459495, Boston College Department of Economics.
    • Handle: RePEc:boc:bocode:s459495
    Note: This module should be installed from within Stata by typing "ssc install kmsenspec". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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    File URL: http://fmwww.bc.edu/repec/bocode/k/kmsenspec.sthlp
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    File URL: http://fmwww.bc.edu/repec/bocode/k/kmsenspec_p.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/k/kmsenspec.pdf
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