Tratamiento de los valores no disponibles
Speaker: Jose Maria Sánchez Sáez
missing varlist, analysis method (method-option) [time-series-option]
missing examines and replaces missing values for the variables
analysis displays a table of association measures.
Specifically, Simple and Jaccard coefficients and their significance levels
are calculated. High coefficient values correspond to strong relationships
method(method-option) specifies the method used for replacing missing values in varlist. Available methods are
In order to sort by date the time-series option is required:
- drop drops observations for which any variable takes on
- impute makes use of the impute ado-file for performing
best subset regression. Since regression does not assume causality, each
variable is modelled as a combination of the rest.
- inter[varname] replaces missing values with linear
interpolations of the existing values for each group defined by varname.
When the missing values are placed at the beginning (end)
of the group, the first (last) available value of that group is repeated.
Interpolation only makes sense in the case of time series.
- mean[varname] replaces missing values with the mean value
for each group defined by varname.
- predict fits (fit command) a linear model
to all the variables in varlist and replaces missing values with predicted
(predict command) values. Note: that this
method does not assure that all the missing values are filled
- Jain, A. K., R.C. Dubes. 1988.
- Algorithms for Clustering Data. Prentice Hall.