Statistics in Medicine

A note on interval estimation of the relative difference in data with matched pairs

Journal Article

Abstract

For controlled comparative trials with matched pairs, in an attempt to improve the asymptotic interval estimator of the relative difference proposed elsewhere, I develop two asymptotic closed‐form interval estimators with use of the logarithmic transformation and an idea used for deriving Fieller's theorem, respectively. I use Monte Carlo simulation to compare the performance of these three interval estimators. Findings reveal that when the number of pairs is as small as 20, the asymptotic interval estimator with use of the logarithmic transformation can actually perform quite well and is generally preferable to the other two asymptotic interval estimators with respect to both the coverage probability and the average length of the resulting confidence intervals. When the number of pairs is large (n⩾100), results show that the three interval estimators considered here are all appropriate for use; they are essentially equivalent in a variety of situations. © 1998 John Wiley & Sons, Ltd.

Related Topics

Related Publications

Related Content

Site Footer

Address:

This website is provided by John Wiley & Sons Limited, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ (Company No: 00641132, VAT No: 376766987)

Published features on StatisticsViews.com are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and StatisticsViews.com express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.