The analysis of incomplete data in the three-period two-treatment cross-over design for clinical trials.

Abstract:

:The additional time to complete a three-period two-treatment (3P2T) cross-over trial may cause a greater number of patient dropouts than with a two-period trial. This paper develops maximum likelihood (ML), single imputation and multiple imputation missing data analysis methods for the 3P2T cross-over designs. We use a simulation study to compare and contrast these methods with one another and with the benchmark method of missing data analysis for cross-over trials, the complete case (CC) method. Data patterns examined include those where the missingness differs between the drug types and depends on the unobserved data. Depending on the missing data mechanism and the rate of missingness of the data, one can realize substantial improvements in information recovery by using data from the partially completed patients. We recommend these approaches for the 3P2T cross-over designs.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Richardson BA,Flack VF

doi

10.1002/(SICI)1097-0258(19960130)15:2<127::AID-SIM

subject

Has Abstract

pub_date

1996-01-30 00:00:00

pages

127-43

issue

2

eissn

0277-6715

issn

1097-0258

pii

10.1002/(SICI)1097-0258(19960130)15:2<127::AID-SIM

journal_volume

15

pub_type

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