# Estimation Methods for Replacing Missing Values

**Series mean.** Replaces
missing values with the mean for the entire series.

**Mean of nearby
points.** Replaces missing values with the mean of valid
surrounding values. The span of nearby points is the number of valid
values above and below the missing value used to compute the mean.

**Median of nearby
points.** Replaces missing values with the median of valid
surrounding values. The span of nearby points is the number of valid
values above and below the missing value used to compute the median.

**Linear interpolation.** Replaces missing values using a linear interpolation. The last valid
value before the missing value and the first valid value after the
missing value are used for the interpolation. If the first or last
case in the series has a missing value, the missing value is not replaced.

**Linear trend at
point.** Replaces missing values with the linear trend for
that point. The existing series is regressed on an index variable
scaled 1 to *n*. Missing values
are replaced with their predicted values.