Format

Send to

Choose Destination
See comment in PubMed Commons below
Psychiatr Ann. 2008 Dec 1;38(12):793-801.

Missing Data in Longitudinal Trials - Part B, Analytic Issues.

Author information

1
Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago.

Abstract

Longitudinal designs in psychiatric research have many benefits, including the ability to measure the course of a disease over time. However, measuring participants repeatedly over time also leads to repeated opportunities for missing data, either through failure to answer certain items, missed assessments, or permanent withdrawal from the study. To avoid bias and loss of information, one should take missing values into account in the analysis. Several popular ways that are now being used to handle missing data, such as the last observation carried forward (LOCF), often lead to incorrect analyses. We discuss a number of these popular but unprincipled methods and describe modern approaches to classifying and analyzing data with missing values. We illustrate these approaches using data from the WECare study, a longitudinal randomized treatment study of low income women with depression.

PMID:
19668352
PMCID:
PMC2722118
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for PubMed Central
    Loading ...
    Support Center