Last observation carried forward (LOCF)

Last observation carried forward (LOCF)

This method is specific to longitudinal data problems. For each individual, missing values are replaced by the last observed value of that variable.

For example: Here the three missing values for unit 1, at times 4, 5 and 6 are replaced by the value at time 3, namely 2.0. Likewise the two missing values for unit 3, at times 5 and 6, are replaced by the value at time 4, which is 3.5. Using LOCF, once the data set has been completed in this way it is analysed as if it were fully observed.

For full longitudinal data analyses this is clearly disastrous: means and covariance structure are seriously distorted.

For single time point analyses the means are still likely to be distorted, measures of precision are wrong and hence inferences are wrong. Note this is true even if the mechanism that causes the data to be missing is completely random.

Reference: www.missingdata.org.uk