Type I and Type II error rates in the last observation carried forward method under informative dropout

Chandan Saha, Michael P. Jones

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Dropout is a persistent problem for a longitudinal study. We exhibit the shortcomings of the last observation carried forward method. It produces biased estimates of change in an outcome from baseline to study endpoint under informative dropout. We developed a theoretical quantification of the effect of such bias on type I and type II error rates. We present results for a setup where a subject either completes the study or drops out during one particular interval, and also under the setup in which subjects could drop out at any time during the study. The type I error rate steadily increases when time to dropout decreases or the common sample size increases. The inflation in type I error rate can be substantially high when reasons for dropout in the two groups differ; when there is a large difference in dropout rates between the control and treatment groups and when the common sample size is large; even when dropout subjects have one or two fewer observations than the completers. Similar results are also observed for type II error rates. A study can have very low power when early recovered patients in the treatment group and worsening patients in the control group drop out even near the end of the study.

Original languageEnglish (US)
Pages (from-to)336-350
Number of pages15
JournalJournal of Applied Statistics
Volume43
Issue number2
DOIs
StatePublished - Jan 25 2016

Keywords

  • LOCF
  • clinical trial
  • incomplete data
  • informative dropout
  • longitudinal study
  • repeatedmeasurements

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Fingerprint Dive into the research topics of 'Type I and Type II error rates in the last observation carried forward method under informative dropout'. Together they form a unique fingerprint.

  • Cite this