PROC SURVEYMEANS
<options> statistickeywords ;
The PROC SURVEYMEANS statement invokes the SURVEYMEANS procedure. In this statement, you identify the data set to be analyzed, specify the variance estimation method, and provide sample design information. The DATA= option names the input data set to be analyzed. The VARMETHOD= option specifies the variance estimation method, which is the Taylor series method by default. For Taylor series variance estimation, you can include a finite population correction factor in the analysis by providing either the sampling rate or population total with the RATE= or TOTAL= option. If your design is stratified, with different sampling rates or totals for different strata, then you can input these stratum rates or totals in a SAS data set that contains the stratification variables.
In the PROC SURVEYMEANS statement, you also can use statistickeywords to specify statistics, such as population mean and population total, for PROC SURVEYMEANS to compute. You can also request data set summary information and sample design information.
Table 96.2 summarizes the options available in the PROC SURVEYMEANS statement.
Table 96.2: PROC SURVEYMEANS Statement Options
Option 
Description 

Sets the confidence level for confidence limits 

Specifies the SAS data set to be analyzed 

Treats missing values as a valid 

Computes variance estimates by analyzing the nonmissing values as a domain 

Requests nonsymmetric confidence limits for quantiles 

Suppresses the display of analysis variables with zero frequency 

Specifies the order in which to report the values of the categorical variables 

Specifies percentiles that you want the procedure to compute 

Requests plots from ODS Graphics 

Specifies quantiles that you want the procedure to compute 

Specifies the sampling rate 

Produces the output data sets by using a stacking table structure 

Specifies the total number of primary sampling units 

Specifies the variance estimation method 
You can specify the following options in the PROC SURVEYMEANS statement:
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.
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.
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.
requests that PROC SURVEYMEANS 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. For more details, see the section Missing Values.
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.
requests nonsymmetric confidence limits for quantiles when you request quantiles with PERCENTILE= or QUANTILE= option. This option applies only to the default VARMETHOD=TAYLOR option. For more details, see the section Confidence Limits.
suppresses the display of analysis variables with zero frequency. By default, the procedure displays all continuous variables and all levels of categorical variables.
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:
orders values according to their order in the input data set.
orders values by their formatted values. This order is operating environment dependent. By default, the order is ascending.
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.
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. For more details, see the section Quantiles.
controls the plots that are produced through ODS Graphics.
A plotrequest identifies the plot, and a plotoption controls the appearance and content of the plot. You can specify plotoptions in parentheses after a plotrequest. A globalplotoption applies to all plots for which it is available. You can specify globalplotoptions in parentheses after the PLOTS option.
When you specify only one plotrequest, you can omit the parentheses around it. Here are a few examples of requesting plots:
plots=all plots(unpack)=summary plots=(summary(unpack) domain) plots=boxplot plots=(domain(packvar) histogram)
You can suppress default plots and request specific plots by specifying the PLOTS(ONLY)= option; PLOTS(ONLY)=(plotrequests) produces only the plots that are specified as plotrequests.
ODS Graphics must be enabled before you can request plots. For example:
ods graphics on; proc surveymeans plots=boxplot; variable income; run; ods graphics off;
For more information about enabling and disabling ODS Graphics, see the section Enabling and Disabling ODS Graphics in Chapter 21: Statistical Graphics Using ODS.
When ODS Graphics is enabled but you do not specify the PLOTS= option, PROC SURVEYMEANS produces summary plots, and it also produces domain plots when you specify a DOMAIN statement. You can suppress all plots by specifying PLOTS=NONE.
For a continuous analytical variable, PROC SURVEYMEANS provides a summary plot, which contains a box plot and a histogram plot. For a categorical variable, PROC SURVEYFREQ provides corresponding plots for it.
For general information about ODS Graphics, see Chapter 21: Statistical Graphics Using ODS.
Global Plot Option
A globalplotoption applies to all plots for which the option is available. You can specify the following globalplotoptions:
suppresses the default plots and requests only the plots that are specified as plotrequests.
specifies the number of bins in a histogram plot. If you do not specify this option, then by default the number of bins is determined by the method of Terrell and Scott (1985).
requests that the procedure create a histogram with overlaid densities and a box plot along with a confidence interval band separately.
Plot Requests
You can specify the following plotrequests:
requests all appropriate plots.
requests box plots for domain statistics for each domain definition. By default, the procedure plots each domain in a single panel for all continuous analysis variables. This plot is produced by default if you specify a DOMAIN statement. You can specify the following plotoptions:
requests that the procedure create box plots for every domain level of a domain but exclude the box plot for the full sample. By default, the box plot includes the full sample box plot.
requests box plots for all domain definitions in one panel for each analytical variable.
requests box plots for all analytical variables in one panel for each domain definition. This is the default when you do not specify the UNPACK option.
requests a box plot for each domain and for each analytical variable in a single panel.
requests a histogram with overlaid normal and kernel densities. You can specify the following plotoption:
specifies the number of bins in a histogram plot. If you do not specify this option, then by default the number of bins is determined by the method of Terrell and Scott (1985).
suppresses all plots.
requests that a histogram and a box plot be displayed together in a single panel, sharing the same X axis. This packed plot is produced by default. You can specify the following plotoptions:
specifies the number of bins in a histogram plot. If you do not specify this option, then by default the number of bins is determined by the method of Terrell and Scott (1985).
requests that a histogram with overlaid densities be displayed in one panel and a box plot along with a confidence interval band be displayed separately. Note that specifying PLOTS(ONLY)=SUMMARY(UNPACK) is exactly the same as specifying PLOTS(ONLY)=(BOX HISTOGRAM).
PLOTS=SUMMARY overwrites the PLOTS=BOX and the PLOTS=HISTOGRAM plotrequests. That is, if you do not specify the UNPACK option, PROC SURVEYMEANS does not display a histogram plot or a box plot by itself when PLOTS=SUMMARY is specified.
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. For more details, see the section Quantiles.
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. For more details, see the section Specification of Population Totals and Sampling Rates.
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.
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
For more details, see the section Rectangular and Stacking Structures in an Output Data Set.
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. For more details, see the section Specification of Population Totals and Sampling Rates.
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.
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. For more information, see the section CLASS Statement.
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. For more information, see the section Missing Values.
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.
You can specify the following statistickeywords:
requests all available statistics except those that are associated with geometric means.
requests all available statistics that are associated with geometric means.
requests the % twosided confidence limits for MEAN, where is determined by the ALPHA= option; the default is .
requests the % twosided confidence limits for SUM, where is determined by the ALPHA= option; the default is .
requests the coefficient of variation for MEAN.
requests the coefficient of variation for SUM.
requests the 10th through the 90th percentiles, including their standard errors and confidence limits.
requests the degrees of freedom for the t test.
requests the geometric mean of a numeric variable that contains positive values.
requests the % twosided confidence limits for GEOMEAN, where is determined by the ALPHA= option; the default is .
requests the standard error of GEOMEAN. When you specify GEOMEAN, SURVEYMEANS procedure computes GMSTDERR by default.
requests the % onesided lower confidence limit for MEAN, where is determined by the ALPHA= option; the default is .
requests the % onesided lower confidence limit for SUM, where is determined by the ALPHA= option; the default is .
requests the % onesided lower confidence limit for GEOMEAN, where is determined by the ALPHA= option; the default is .
requests the maximum value.
requests the mean for a numeric variable, or the proportion in each category for a categorical variable.
requests the median (50th percentile) for a numeric variable.
requests the minimum value.
requests the number of clusters.
requests the number of missing observations.
requests the number of nonmissing observations.
requests the lower quartile (25th percentile).
requests the upper quartile (75th percentile).
requests Q1 (25th percentile), MEDIAN (50th percentile), and Q3 (75th percentile), including their standard errors and confidence limits.
requests the range, MAX–MIN.
requests the ratio of means or proportions.
requests the standard deviation of SUM. When you request SUM, the procedure computes STD by default.
requests the standard error of MEAN or RATIO. When you request MEAN or RATIO, the procedure computes STDERR by default.
requests the weighted sum, , or estimated population total when the appropriate sampling weights are used.
requests the sum of the weights, .
requests the t value and its corresponding pvalue with DF degrees of freedom for , where is a requested statistic.
requests the % onesided upper confidence limit for MEAN, where is determined by the ALPHA= option; the default is .
requests the % onesided upper confidence limit for SUM, where is determined by the ALPHA= option; the default is .
requests the % onesided upper confidence limit for GEOMEAN, where is determined by the ALPHA= option; the default is .
requests the variance of MEAN or RATIO.
requests the variance of SUM.
For details about how PROC SURVEYMEANS computes these statistics, see the section Statistical Computations.
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 96.3 summarizes the available methodoptions.
Table 96.3: Variance Estimation Options
VARMETHOD= 
Variance Estimation Method 
MethodOptions 

BRR 

JACKKNIFE 

TAYLOR 
Taylor series linearization 
None 
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:
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:
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.
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.
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.
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.
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.
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.
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:
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.
names a SAS data set that contains jackknife coefficients. See the section Jackknife Method for information about jackknife coefficients. See the section Jackknife Coefficients Output Data Set for more details about the contents of the OUTJKCOEFS= data set.
names a SAS data set that contains replicate weights. See the section Jackknife 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.
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.