Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If You Use a Screen Reader

This content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.

Evaluation of Exact and Asymptotic Interval Estimators in Logistic Analysis of Matched Case-Control Studies

Stein E. Vollset, Karim F. Hirji and Abdelmonem A. Afifi
Biometrics
Vol. 47, No. 4 (Dec., 1991), pp. 1311-1325
DOI: 10.2307/2532388
Stable URL: http://www.jstor.org/stable/2532388
Page Count: 15
  • Read Online (Free)
  • Download ($14.00)
  • Subscribe ($19.50)
  • Cite this Item
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Evaluation of Exact and Asymptotic Interval Estimators in Logistic Analysis of Matched Case-Control Studies
Preview not available

Abstract

We compare six methods for constructing confidence intervals for a single parameter in stratified logistic regression. Three of these are based on inversion of standard asymptotic tests-namely, the Wald, the score, and the likelihood ratio tests. The other three are based on the exact distribution of the sufficient statistic for the parameter of interest. These include the traditional exact method of constructing confidence intervals, and two others, the mid-P and mean-P methods, which are modifications of this procedure that aim at reducing the conservative bias of the exact method. Using efficient algorithms, the six methods are compared by determination of their exact coverage levels in a series of conditional sample spaces. An incident case-control study of lung cancer in women is used to further illustrate the differences among the various methods. Computation of coverage functions is seen as a useful graphical diagnostic tool for assessing the appropriateness of different methods. The mid-P and the score methods are seen to have better coverage properties than the other four.

Page Thumbnails

  • Thumbnail: Page 
1311
    1311
  • Thumbnail: Page 
1312
    1312
  • Thumbnail: Page 
1313
    1313
  • Thumbnail: Page 
1314
    1314
  • Thumbnail: Page 
1315
    1315
  • Thumbnail: Page 
1316
    1316
  • Thumbnail: Page 
1317
    1317
  • Thumbnail: Page 
1318
    1318
  • Thumbnail: Page 
1319
    1319
  • Thumbnail: Page 
1320
    1320
  • Thumbnail: Page 
1321
    1321
  • Thumbnail: Page 
1322
    1322
  • Thumbnail: Page 
1323
    1323
  • Thumbnail: Page 
1324
    1324
  • Thumbnail: Page 
1325
    1325