
ALPHA=

sets the confidence level for confidence limits. The value of the ALPHA= option must be between 0 and 1, and the default value
is 0.05. A confidence level of produces % confidence limits. The default of ALPHA=0.05 produces 95% confidence limits.

DATA=SASdataset

specifies the SAS data set to be analyzed by PROC SURVEYMEANS. If you omit the DATA= option, the procedure uses the most recently
created SAS data set.

MISSING

treats missing values as a valid (nonmissing) category for all categorical variables, which include CLASS, STRATA, CLUSTER, DOMAIN, and POSTSTRATA variables.
By default, if you do not specify the MISSING option, an observation is excluded from the analysis if it has a missing value.
For more information, see the section Missing Values.

NOMCAR

requests that the procedure treat missing values in the variance computation as not missing completely at random (NOMCAR) for Taylor series variance estimation. When you specify the NOMCAR option, PROC SURVEYMEANS computes variance estimates
by analyzing the nonmissing values as a domain (subpopulation), where the entire population includes both nonmissing and missing
domains. See the section Missing Values for more details.
By default, PROC SURVEYMEANS completely excludes an observation from analysis if that observation has a missing value, unless
you specify the MISSING option for categorical variables. Note that the NOMCAR option has no effect on a categorical variable when you specify the
MISSING option, which treats missing values as a valid nonmissing level.
The NOMCAR option applies only to Taylor series variance estimation. The replication methods, which you request with the VARMETHOD=BRR and VARMETHOD=JACKKNIFE options, do not use the NOMCAR option.
The NOMCAR option is not available for geometric means or poststratification.

NONSYMCL

requests nonsymmetric confidence limits for quantiles when you request quantiles with PERCENTILE= or QUANTILE= option. See the section Confidence Limits for more details. This option applies only to the default VARMETHOD=TAYLOR option.

NOSPARSE

suppresses the display of analysis variables with zero frequency. By default, the procedure displays all continuous variables
and all levels of categorical variables.

ORDER=DATA  FORMATTED  INTERNAL

specifies the order in which the values of the categorical variables are to be reported.
This option also determines the sort order for the levels of ClUSTER and DOMAIN variables and controls STRATA variable levels
in the “Stratum Information” table.
The following shows how PROC SURVEYMEANS interprets values of the ORDER= option:
 DATA

orders values according to their order in the input data set.
 FORMATTED

orders values by their formatted values. This order is operating environment dependent. By default, the order is ascending.
 INTERNAL

orders values by their unformatted values, which yields the same order that the SORT procedure does. This order is operating
environment dependent.
By default, ORDER=INTERNAL. For ORDER=FORMATTED and ORDER=INTERNAL, the sort order is machinedependent.
For more information about sort order, see the chapter on the SORT procedure in the
Base SAS Procedures Guide and the discussion of BYgroup processing in
SAS Language Reference: Concepts.

PERCENTILE=(values)

specifies percentiles you want the procedure to compute. You can separate values with blanks or commas. Each value must be
between 0 and 100. You can also use the statistickeywords DECILES, MEDIAN, Q1, Q3, and QUARTILES to request common percentiles.
PROC SURVEYMEANS uses Woodruff’s method (Dorfman and Valliant, 1993; Särndal, Swensson, and Wretman, 1992; Francisco and Fuller, 1991) to estimate the variances of quantiles. See the section Quantiles for more details.

QUANTILE=(values)

specifies quantiles you want the procedure to compute. You can separate values with blanks or commas. Each value must be between
0 and 1. You can also use the statistickeywords DECILES, MEDIAN, Q1, Q3, and QUARTILES to request common quantiles.
PROC SURVEYMEANS uses Woodruff’s method (Dorfman and Valliant, 1993; Särndal, Swensson, and Wretman, 1992; Francisco and Fuller, 1991) to estimate the variances of quantiles. See the section Quantiles for more details.

RATE=value  SASdataset
R=value  SASdataset

specifies the sampling rate as a nonnegative value, or specifies an input data set that contains the stratum sampling rates. The procedure uses this information to compute
a finite population correction for Taylor series variance estimation. The procedure does not use the RATE= option for BRR
or jackknife variance estimation, which you request with the VARMETHOD=BRR or VARMETHOD=JACKKNIFE option.
If your sample design has multiple stages, you should specify the firststage sampling rate, which is the ratio of the number of PSUs selected to the total number of PSUs in the population.
For a nonstratified sample design, or for a stratified sample design with the same sampling rate in all strata, you should
specify a nonnegative value for the RATE= option. If your design is stratified with different sampling rates in the strata, then you should name a SAS
data set that contains the stratification variables and the sampling rates. See the section Specification of Population Totals and Sampling Rates for more details.
The value in the RATE= option or the values of _RATE_
in the secondary data set must be nonnegative numbers. You can specify value as a number between 0 and 1. Or you can specify value in percentage form as a number between 1 and 100, and PROC SURVEYMEANS converts that number to a proportion. The procedure
treats the value 1 as 100% instead of 1%.
If you do not specify the TOTAL= or RATE= option, then the Taylor series variance estimation does not include a finite population correction. You cannot specify
both the TOTAL= and RATE= options.

STACKING

requests that the procedure produce the output data sets by using a stacking table structure, which was the default before
SAS 9. The new default is to produce a rectangular table structure in the output data sets.
A rectangular structure creates one observation for each analysis variable in the data set. A stacking structure creates only
one observation in the output data set for all analysis variables.
The STACKING option affects the following tables:

Domain

Ratio

Statistics

StrataInfo
See the section Rectangular and Stacking Structures in an Output Data Set for more details.

TOTAL=value  SASdataset
N=value  SASdataset

specifies the total number of primary sampling units in the study population as a positive value, or specifies an input data set that contains the stratum population totals. The procedure uses this information to compute
a finite population correction for Taylor series variance estimation. The procedure does not use the TOTAL= option for BRR
or jackknife variance estimation, which you request with the VARMETHOD=BRR or VARMETHOD=JACKKNIFE option.
For a nonstratified sample design, or for a stratified sample design with the same population total in all strata, you should
specify a positive value for the TOTAL= option. If your sample design is stratified with different population totals in the strata, then you should
name a SAS data set that contains the stratification variables and the population totals. See the section Specification of Population Totals and Sampling Rates for more details.
If you do not specify the TOTAL= or RATE= option, then the Taylor series variance estimation does not include a finite population correction. You cannot specify both
the TOTAL= and RATE= options.

statistickeywords

specifies the statistics for the procedure to compute. If you do not specify any statistickeywords, PROC SURVEYMEANS computes the NOBS, MEAN, STDERR, and CLM statistics by default.
The statistics produced depend on the type of the analysis variable. If you name a numeric variable in the CLASS statement,
then the procedure analyzes that variable as a categorical variable. The procedure always analyzes character variables as
categorical. See the section CLASS Statement for more information.
PROC SURVEYMEANS computes MIN, MAX, and RANGE for numeric variables but not for categorical variables. For numeric variables,
the keyword MEAN produces the mean, but for categorical variables it produces the proportion in each category or level. Also,
for categorical variables, the keyword NOBS produces the number of observations for each variable level, and the keyword NMISS
produces the number of missing observations for each level. If you request the keyword NCLUSTER for a categorical variable,
PROC SURVEYMEANS displays for each level the number of clusters with observations in that level. PROC SURVEYMEANS computes
SUMWGT in the same way for both categorical and numeric variables, as the sum of the weights over all nonmissing observations.
PROC SURVEYMEANS performs univariate analysis, analyzing each variable separately. Thus the number of nonmissing and missing
observations might not be the same for all analysis variables. See the section Missing Values for more information.
The following statistics are available for ratios (which you request with a RATIO statement): N, NCLU, SUMWGT, RATIO, STDERR, DF, T, PROBT, and CLM, as shown in the following list. If no statistics are requested,
the procedure computes the ratio and its standard error by default.
The valid statistickeywords are as follows:
 ALL

all available statistics except those associated with geometric means
 ALLGEO

all available statistics associated with geometric means
 CLM

% twosided confidence limits for the MEAN, where is determined by the ALPHA= option; the default is
 CLSUM

% twosided confidence limits for the SUM, where is determined by the ALPHA= option; the default is
 CV

coefficient of variation for MEAN
 CVSUM

coefficient of variation for SUM
 DECILES

the 10th, the 20th, …, and the 90th percentiles including their standard errors and confidence limits
 DF

degrees of freedom for the t test
 GEOMEAN

geometric mean of a numeric variable that contains positive values
 GMCLM

% twosided confidence limits for the GEOMEAN, where is determined by the ALPHA= option; the default is
 GMSTDERR

standard error of the GEOMEAN. When you request GEOMEAN, the procedure computes GMSTDERR by default.
 LCLM

% onesided lower confidence limit for the MEAN, where is determined by the ALPHA= option; the default is
 LCLSUM

% onesided lower confidence limit for the SUM, where is determined by the ALPHA= option; the default is
 LGMCLM

% onesided lower confidence limit for the GEOMEAN, where is determined by the ALPHA= option; the default is
 MAX

maximum value
 MEAN

mean for a numeric variable, or the proportion in each category for a categorical variable
 MEDIAN

median for a numeric variable
 MIN

minimum value
 NCLUSTER

number of clusters
 NMISS

number of missing observations
 NOBS

number of nonmissing observations
 Q1

lower quartile
 Q3

upper quartile
 QUARTILES

lower quartile (25%th percentile), median (50%th percentile), and upper quartile (75%th percentile), including their standard
errors and confidence limits
 RANGE

range, MAX–MIN
 STD

standard deviation of the SUM. When you request SUM, the procedure computes STD by default.
 STDERR

standard error of the MEAN or RATIO. When you request MEAN or RATIO, the procedure computes STDERR by default.
 SUM

weighted sum, , or estimated population total when the appropriate sampling weights are used
 SUMWGT

sum of the weights,
 T

tvalue and its corresponding pvalue with DF degrees of freedom for , where is a requested statistic
 UCLM

% onesided upper confidence limit for the MEAN, where is determined by the ALPHA= option; the default is
 UCLSUM

% onesided upper confidence limit for the SUM, where is determined by the ALPHA= option; the default is
 UGMCLM

% onesided upper confidence limit for the GEOMEAN, where is determined by the ALPHA= option; the default is
 VAR

variance of the MEAN or RATIO
 VARSUM

variance of the SUM
See the section Statistical Computations for details about how PROC SURVEYMEANS computes these statistics.

VARMETHOD=BRR <(methodoptions)>
VARMETHOD=JACKKNIFE  JK <(methodoptions)>
VARMETHOD=TAYLOR

specifies the variance estimation method. VARMETHOD=TAYLOR requests the Taylor series method, which is the default if you
do not specify the VARMETHOD= option or the REPWEIGHTS statement. VARMETHOD=BRR requests variance estimation by balanced repeated
replication (BRR), and VARMETHOD=JACKKNIFE requests variance estimation by the delete1 jackknife method.
For VARMETHOD=BRR and VARMETHOD=JACKKNIFE you can specify methodoptions in parentheses. Table 92.3 summarizes the available methodoptions.
Table 92.3: Variance Estimation Options
Methodoptions must be enclosed in parentheses following the method keyword. For example:
varmethod=BRR(reps=60 outweights=myReplicateWeights)
The following values are available for the VARMETHOD= option:
 BRR <(methodoptions)>

requests balanced repeated replication (BRR) variance estimation. The BRR method requires a stratified sample design with two primary sampling units (PSUs) per
stratum. See the section Balanced Repeated Replication (BRR) Method for more information.
You can specify the following methodoptions in parentheses following VARMETHOD=BRR:

DFADJ

computes the degrees of freedom as the number of nonmissing strata for an analysis variable. The degrees of freedom for VARMETHOD=BRR
equal the number of strata, which by default is based on all valid observations in the data set. But if you specify the DFADJ
methodoption, PROC SURVEYMEANS does not count any empty strata that are due to all observations containing missing values for an analysis
variable.
See the section Degrees of Freedom for more information. See the section Data and Sample Design Summary for details about valid observations.
The DFADJ methodoption has no effect on categorical variables when you specify the MISSING option, which treats missing values as a valid nonmissing level.
The DFADJ methodoption cannot be used when you provide replicate weights with a REPWEIGHTS statement. When you use a REPWEIGHTS statement, the degrees of freedom equal the number of REPWEIGHTS variables (or replicates),
unless you specify an alternative value in the DF= option in the REPWEIGHTS statement.

FAY <=value>

requests Fay’s method, a modification of the BRR method, for variance estimation. See the section Fay’s BRR Method for more information.
You can specify the value of the Fay coefficient, which is used in converting the original sampling weights to replicate weights. The Fay coefficient
must be a nonnegative number less than 1. By default, the value of the Fay coefficient equals 0.5.

HADAMARD=SASdataset
H=SASdataset

names a SAS data set that contains the Hadamard matrix for BRR replicate construction. If you do not provide a Hadamard matrix with the HADAMARD= methodoption, PROC SURVEYMEANS generates an appropriate Hadamard matrix for replicate construction. See the sections Balanced Repeated Replication (BRR) Method and Hadamard Matrix for details.
If a Hadamard matrix of a given dimension exists, it is not necessarily unique. Therefore, if you want to use a specific Hadamard
matrix, you must provide the matrix as a SAS data set in the HADAMARD= methodoption.
In the HADAMARD= input data set, each variable corresponds to a column of the Hadamard matrix, and each observation corresponds
to a row of the matrix. You can use any variable names in the HADAMARD= data set. All values in the data set must equal either
1 or –1. You must ensure that the matrix you provide is indeed a Hadamard matrix—that is, , where is the Hadamard matrix of dimension R and is an identity matrix. PROC SURVEYMEANS does not check the validity of the Hadamard matrix that you provide.
The HADAMARD= input data set must contain at least H variables, where H denotes the number of firststage strata in your design. If the data set contains more than H variables, the procedure uses only the first H variables. Similarly, the HADAMARD= input data set must contain at least H observations.
If you do not specify the REPS= methodoption, then the number of replicates is taken to be the number of observations in the HADAMARD= input data set. If you specify
the number of replicates—for example, REPS=nreps—then the first nreps observations in the HADAMARD= data set are used to construct the replicates.
You can specify the PRINTH option to display the Hadamard matrix that the procedure uses to construct replicates for BRR.

OUTWEIGHTS=SASdataset

names a SAS data set that contains replicate weights. See the section Balanced Repeated Replication (BRR) Method for information about replicate weights. See the section Replicate Weights Output Data Set for more details about the contents of the OUTWEIGHTS= data set.
The OUTWEIGHTS= methodoption is not available when you provide replicate weights with the REPWEIGHTS statement.

PRINTH

displays the Hadamard matrix.
When you provide your own Hadamard matrix with the HADAMARD= methodoption, only the rows and columns of the Hadamard matrix that are used by the procedure are displayed. See the sections Balanced Repeated Replication (BRR) Method and Hadamard Matrix for details.
The PRINTH methodoption is not available when you provide replicate weights with the REPWEIGHTS statement because the procedure does not use a Hadamard matrix in this case.

REPS=number

specifies the number of replicates for BRR variance estimation. The value of number must be an integer greater than 1.
If you do not provide a Hadamard matrix with the HADAMARD= methodoption, the number of replicates should be greater than the number of strata and should be a multiple of 4. See the section Balanced Repeated Replication (BRR) Method for more information. If a Hadamard matrix cannot be constructed for the REPS= value that you specify, the value is increased
until a Hadamard matrix of that dimension can be constructed. Therefore, it is possible for the actual number of replicates
used to be larger than the REPS= value that you specify.
If you provide a Hadamard matrix with the HADAMARD= methodoption, the value of REPS= must not be less than the number of rows in the Hadamard matrix. If you provide a Hadamard matrix and
do not specify the REPS= methodoption, the number of replicates equals the number of rows in the Hadamard matrix.
If you do not specify the REPS= or HADAMARD= methodoption and do not include a REPWEIGHTS statement, the number of replicates equals the smallest multiple of 4 that is greater than the number of strata.
If you provide replicate weights with the REPWEIGHTS statement, the procedure does not use the REPS= methodoption. With a REPWEIGHTS statement, the number of replicates equals the number of REPWEIGHTS variables.
 JACKKNIFE  JK <(methodoptions)>

requests variance estimation by the delete1 jackknife method. See the section Jackknife Method for details. If you provide replicate weights with a REPWEIGHTS statement, VARMETHOD=JACKKNIFE is the default variance estimation method.
You can specify the following methodoptions in parentheses following VARMETHOD=JACKKNIFE:

DFADJ

computes the degrees of freedom as the number of nonmissing strata for an analysis variable. The degrees of freedom for VARMETHOD=JACKKNIFE
equal the number of clusters (or number of observations if there is no clusters) minus the number of strata (or one if there
is no strata). By default, the number of strata is based on all valid observations in the data set. But if you specify the
DFADJ methodoption, PROC SURVEYMEANS does not count any empty strata that are due to all observations containing missing values for an analysis
variable.
See the section Degrees of Freedom for more information. See the section Data and Sample Design Summary for details about valid observations.
The DFADJ methodoption has no effect on categorical variables when you specify the MISSING option, which treats missing values as a valid nonmissing level.
The DFADJ methodoption cannot be used when you provide replicate weights with a REPWEIGHTS statement. When you use a REPWEIGHTS statement, the degrees of freedom equal the number of REPWEIGHTS variables (or replicates),
unless you specify an alternative value in the DF= option in the REPWEIGHTS statement.
 TAYLOR

requests Taylor series variance estimation. This is the default method if you do not specify the VARMETHOD= option or a REPWEIGHTS statement. See the section Taylor Series Method for more information.