Table 1. Imputation methods for longitudinal data.

Imputation methods	Brief description
Cross sectional imputation
Cross mean	Replace missing value with mean of values observed at that time
Cross median	Replace missing value with median of values observed at that time
Cross hot deck	Replace missing value with a randomly chosen value among values observed at that time
Longitudinal imputation
Traj mean	Replace missing value by average values of that subject (trajectory)
Traj median	Replace missing value by median value of that subject (trajectory)
Traj hot deck	Replace missing value by a value chosen randomly from that subject (trajectory)
LOCF	Replace missing value by previous non-missing value of that subject (trajectory)
Linear interpolation	Values immediately surrounding the missing are join by a line
Spline interpolation	Values immediately surrounding the missing are joined by a cubic spline
Cross and longitudinal imputation
Copy mean	Combine linear interpolation and imputation using population’s mean trajectory
Linear regression	Predict missing value by constructing a model

LOCF, last occurrence carried forward.