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The MEANS Procedure

WEIGHT Statement

Specifies weights for observations in the statistical calculations.
See also: For information on how to calculate weighted statistics and for an example that uses the WEIGHT statement, see WEIGHT

WEIGHT variable;

Required Arguments


specifies a numeric variable whose values weight the values of the analysis variables. The values of the variable do not have to be integers. If the value of the weight variable is

Weight value... PROC MEANS...
0 counts the observation in the total number of observations
less than 0 converts the value to zero and counts the observation in the total number of observations
missing excludes the observation

To exclude observations that contain negative and zero weights from the analysis, use EXCLNPWGT. Note that most SAS/STAT procedures, such as PROC GLM, exclude negative and zero weights by default.

Restriction: To compute weighted quantiles, use QMETHOD=OS in the PROC statement.
Restriction: Skewness and kurtosis are not available with the WEIGHT statement.
Restriction: PROC MEANS will not compute MODE when a weight variable is active. Instead, try using The UNIVARIATE Procedure when MODE needs to be computed and a weight variable is active.
Interaction: If you use the WEIGHT= option in a VAR statement to specify a weight variable, then PROC MEANS uses this variable instead to weight those VAR statement variables.
Tip: When you use the WEIGHT statement, consider which value of the VARDEF= option is appropriate. See the discussion of VARDEF= and the calculation of weighted statistics in Keywords and Formulas for more information.

Note:   Before Version 7 of SAS, the procedure did not exclude the observations with missing weights from the count of observations.  [cautionend]

Single extreme weight values can cause inaccurate results.

When one (and only one) weight value is many orders of magnitude larger than the other weight values (for example, 49 weight values of 1 and one weight value of 1×1014), certain statistics might not be within acceptable accuracy limits. The affected statistics are based on the second moment (such as standard deviation, corrected sum of squares, variance, and standard error of the mean). Under certain circumstances, no warning is written to the SAS log.  [cautionend]

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