User Guide

173
Data Transform
ations
To Rep lac e Missing Values for Time S eries Va ria ble s
E From the menus choose:
Transform
Replace Missing Values...
E
Select the estimation method you want to use to replace missing values.
E Select the variable(s) for which you want to replace missing values.
Optionally,
you can:
 Enter varia
ble names to override the default new variable names.
 Change the e
stimation method for a selected variable.
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 valu
e 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 tre
nd at point.
Replaces missing values with the linear trend for that point.
Theexistingseriesisregressedonanindexvariablescaled1ton. Missing values
are replaced with their predicted values.