The STDIZE Procedure
FREQ Statement
Specifies a numeric variable whose values represent the frequency of the observation.
Discussion: If one variable in the input data set represents the frequency of occurrence for other
values in the observation, specify the variable's name in a FREQ statement. PROC
STDIZE then treats the data set as if each observation appeared n times, where n is the
value of the FREQ variable for the observation.
Alias: FREQUENCY
FREQ variable;
Required Argument
variable
Specifies a single numeric variable whose value represents the frequency of the observation. If
you use the FREQ statement, the procedure assumes that each observation represents n
observations, where n is the value of variable.
Range:
If variable is not an integer, the SAS System truncates it to the largest integer
less than the FREQ value. If variable is less than 1 or is missing, the
procedure does not use that observation to calculate statistics. The sum of the
frequency variable represents the total number of observations and cannot
exceed 2
31
.
Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
The STDIZE Procedure
LOCATION Statement
Specifies the list of numeric variables that contain location measures in the input data set of
METHOD=IN.
LOCATION variable(s);
Required Argument
variable(s)
Specifies one or more variables that contain location measures in the input data set identified by
the METHOD=IN(SAS-data-set).
Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
The STDIZE Procedure
SCALE Statement
Specifies the list of numeric variables that contain scale measures in the input data set of
METHOD=IN.
SCALE variable(s);
Required Argument
variable(s)
Identifies one or more variables that contain scale measures in the input data set identified by the
METHOD=IN(SAS-data-set).
Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
The STDIZE Procedure
VAR Statement
Specifies a list of variables to be standardized.
Alias: VARIABLE
Default: If the VAR statement is omitted, all numeric variables not specified in the BY=, FREQ=,
LOCATION=, SCALE=, or WEIGHT= lists are standardized.
VAR variable(s);
Required Argument
variable(s)
Identifies one or more variables to be standardized.
Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
The STDIZE Procedure
WEIGHT Statement
Specifies a single numeric weight in the input SAS data set whose values are used to weight each
observation. Only one variable can be specified.
Alias: WGT
WEIGHT variable;
Required Argument
variable
Specifies a numeric variable whose value weights the analysis variables in each observation. The
variable does not have to be an integer. If the value of variable is less than 0 or is missing, the
procedure uses a value of 0.
Discussion:
The sample mean and (uncorrected) sample variances are computed as:
where
is the weight value of the th observation,
is the value of the th
observation, and is the divisor controlled by the VARDEF=option (see
VARDEF= option for details).
MEAN
the weighted mean
SUM
the weighted sum
USTD
the weighted uncorrected standard deviation,
STD
the weighted standard deviation,
EUCLEN
The weighted Euclidean length is computed as the weighted squared
root of uncorrected sum of squares:
AGK
Refers to the weight statement in PROC ACECLUS for how weight is
applied to the AGK estimate (METHOD=COUNT) option.
L
Refers to the weight statement in PROC FASTCLUS for how weight is
used to compute weighted cluster means (LEAST= option). Note that
the number of clusters is always 1.
Range:
The WEIGHT variable values can be non-integers. An observation is used in
the analysis only if the value of the WEIGHT variable is greater than 0.
Tip:
The WEIGHT variable only affects METHOD=MEAN, SUM, EUCLEN,
USTD, STD, AGK, and L calculations.
Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
The STDIZE Procedure
Details
Standardization Methods
The following table lists standardization methods and their corresponding location and scale measures
that are available in the METHOD= option.
Table of Methods for Computing Location and Scale
Measures
METHOD
SCALE
LOCATION
ABW(c)
Biweight
A-estimate
Biweight 1-step
M-estimate
AGK(p)
AGK
estimate
(ACECLUS)
Mean
AHUBER (c)
Huber
A-estimate
Huber 1-step
M-estimate
AWAVE (c)
Wave
A-estimate
Wave 1-step M
estimate
EUCLEN
Euclidean
length
0
IN(SAS-data-set)
Read from
the data set
Read from the
data set
IQR
Interquartile
range
Median
LEAST
L(p)
L(p)
MAD
Median
absolute
deviation
from the
median
Median
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