For a variety of reasons including poorly designed case report forms (CRFs), incomplete or
invalid CRF data entries, and premature treatment or study discontinuations, missing data is …

A major problem in the analysis of clinical trials is missing data caused by patients dropping
out of the study before completion. This problem can result in biased treatment comparisons …

Missing data in clinical trials are inevitable. We highlight the ICH guidelines and CPMP
points to consider on missing data. Specifically, we outline how we should consider missing …

In recent years, the use of the last observation carried forward (LOCF) approach in imputing
missing data in clinical trials has been greatly criticized, and several likelihood-based …

Missing data, and the bias they can cause, are an almost ever‐present concern in clinical
trials. The last observation carried forward (LOCF) approach has been frequently utilized to …

One of the major problems in the analysis of clinical trials is missing data caused by patients
dropping out before study completion. The issue of missing data can result in biased …

This study compares two methods for handling missing data in longitudinal trials: one using
the last‐observation‐carried‐forward (LOCF) method and one based on a multivariate or …

The issuance of a report in 2010 by the National Research Council (NRC) of the National
Academy of Sciences entitled 'The Prevention and Treatment of Missing Data in Clinical …

Missing values and dropouts are common issues in longitudinal studies in all areas of
medicine and public health. Intent-to-treat (ITT) analysis has become a widely accepted …

The last-observation-carried-forward imputation method is commonly used for imputing data
missing due to dropouts in longitudinal clinical trials. The method assumes that outcome …