The STDIZE procedure standardizes one or more numeric variables in a SAS data set by subtracting a
location measure and dividing by a scale measure. A variety of location and scale measures are provided,
including estimates that are resistant to outliers and clustering (see the METHOD= option). You can also
multiply each standardized value by a constant and add a constant. Thus the result is:
is the final output value
is the constant to add (the value specified in the ADD= option)
is the constant to multiply by (the value specified in the MULT= option)
is the original input value
is the location measure
is the scale measure
very large and PROC UNIVARIATE may either run out of memory or take a long time to compute the
Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
Specifies the constant to add to each value after standardizing and multiplying by the MULT=
Specifies the input data source to be standardized.
Specifies the relative fuzz factor for writing the output.
then result= 0.
For OUTSTAT= data set: if
then SCALE= 0;
Specifies the method for computing initial estimates for the A estimates: ABW, AWAVE, and
AHUBER. See the
Table of Methods for Computing Location and Scale Measures
for the list of
Specifies the name of the standardization method. See
section for more
information on the method-names that are available for computing LOCATION and SCALE
Specifies the method or a numeric value for replacing missing values.
Use the MISSING= option when you want to replace missing values by something other
than the location measure associated with the METHOD= option, which is what the
REPLACE option uses as the replacement value. The usual methods include MEAN,
MEDIAN, and MIDRANGE. Any of the values for the METHOD= option can also be
specified for the MISSING= option, and the corresponding location measure will be used to
replace missing values. If a numeric value is given, it replaces missing values after
standardizing the data. However, the REPONLY option can be used together with the
MISSING= option to suppress standardization in case you only want to replace missing
for a list of the
values that can be specified for the MISSING= option (with the exception of
Specifies the constant to multiply each value by, after standardizing.
Specifies the number of markers for the P2 algorithm (PCTLMTD=P2).
Integer where n 5).
Omits observations that have missing values in the analyzed variables from computation of the
location and scale measures. Otherwise, all nonmissing values are used.
For METHOD= AGK, IQR, MAD, or SPACING, normalizes the scale estimator to be consistent
for the standard deviation of a normal distribution.
Specifies the output data set created by PROC STDIZE. The output data set is a copy of the
of a VAR statement, all numeric variables not listed in any other statement) have been
_DATA_. If the OUT= option is omitted, PROC STDIZE creates an output
data set and names it according to the DATAn convention, just as if you had
omitted a data set name in a DATA statement.
Specifies the output statistics data set that contains the location and scale measures and some other
simple statistics. A _TYPE_ variable is also created to help identify the type of statistics for each
observation. The value of the _TYPE_ variable can be:
Contains the location measure of each variable.
Contains the scale measure of each variable.
Contains the norm measure of each variable.
Contains the constant from the ADD= option.
Contains the constant from the MULT= option.
Contains the total number of non-missing positive frequencies of each variable.
Contains the percentiles of each variable specified through the PCTLPTS= option.
0 n 100
Specifies one of the five available definitions described in the Computational Methods section in
the UNIVARIATE procedure that calculates percentiles when PCTLMTD=ORD_STAT is
1, 2, 3, 4, 5
When PCTLMTD=P2, the value of PCTLDEF is always 5.
Specifies the method used to estimate percentiles.