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ROCMIC: Stata module to estimate minimally important change (MIC) thresholds for continuous clinical outcome measures using ROC curves

Author

Listed:
  • Robert Froud

    (Queen Mary, University of London)

Programming Language

Stata

Abstract

ROCMIC estimates minimally important change (MIC) thresholds using three different methods. The first is the cut-point corresponding to a 45 degree tangent line intersection; this is mathematically equivalent to the point at which the sensitivity and specificity are closest together. The second is the cut-point corresponding to the smallest sum of 1-sensitivity and 1-specificity; this methodology has been proposed by researchers from the EMGO Institute . The third is the cut-point corresponding to the smallest sum of squares of 1-sensitivity and 1-specificity in accordance with Pythagoras' theorem, as has been recommended by the package authors.

Suggested Citation

  • Robert Froud, 2009. "ROCMIC: Stata module to estimate minimally important change (MIC) thresholds for continuous clinical outcome measures using ROC curves," Statistical Software Components S457052, Boston College Department of Economics, revised 24 Oct 2014.
    • Handle: RePEc:boc:bocode:s457052
    Note: This module should be installed from within Stata by typing "ssc install rocmic". 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.
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/r/rocmic.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/r/rocmic.sthlp
    File Function: help file
    Download Restriction: no
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