Using audit information to adjust parameter estimates for data errors in clinical trials.

ABSTRACT:

Background

Audits are often performed to assess the quality of clinical trial data, but beyond detecting fraud or sloppiness, the audit data are generally ignored. In an earlier study, using data from a nonrandomized study, Shepherd and Yu developed statistical methods to incorporate audit results into study estimates and demonstrated that audit data could be used to eliminate bias.

Purpose

In this article, we examine the usefulness of audit-based error-correction methods in clinical trial settings where a continuous outcome is of primary interest.

Methods

We demonstrate the bias of multiple linear regression estimates in general settings with an outcome that may have errors and a set of covariates for which some may have errors and others, including treatment assignm

SUBMITTER: Shepherd BE 

PROVIDER: S-EPMC3728661 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature