The OUTPUT statement applies only to the last plan generated.
If you use PROC PLAN interactively, the OUTPUT statement for a given
plan must be immediately preceded by the FACTORS statement
(and the TREATMENTS statement, if appropriate) for the plan.
See the "Output Data Sets" section for more information on how output data sets are
- OUTPUT OUT=SAS-data-set
< DATA=SAS-data-set >
factor-value-settings > ;
You can specify the following options in the OUTPUT statement:
You can use the OUTPUT statement both to output
the last plan generated and to use the last
plan generated to randomize another SAS data set.
When you specify only the OUT= option in the OUTPUT
statement, PROC PLAN saves the last plan generated to the
specified data set. The output data set contains one variable for
each factor in the plan and one observation for each cell in
the plan. The value of a variable in a given observation is
the level of the corresponding factor for that cell. The
OUT= option is required.
When you specify both the DATA= and OUT= options in the
OUTPUT statement, then PROC PLAN uses the last plan generated to
randomize the input data set (DATA=), saving the results to the
output data set (OUT=). The output data set has the same
form as the input data set but has modified values
for the variables that correspond to factors (see
the "Output Data Sets" section for details). Values for variables not
corresponding to factors are transferred without change.
specify the values input or output for the factors in the design.
The form for factor-value-settings is
different when only an OUT= data set is specified
and when both OUT= and DATA= data sets are specified.
Both forms are discussed in the following section.
Factor-Value-Settings with Only an OUT= Data Set
When you specify only an OUT= data set, the form for each
factor-value-setting specification is one of the following:
- factor-name <
< ORDERED | RANDOM >
- factor-name <
< ORDERED | RANDOM >
- is a factor in the last FACTORS statement preceding the OUTPUT statement.
lists n numeric values for the factor.
By default, the procedure uses NVALS=(1 2 3 ... n).
lists n character strings for the factor.
Each string can have up to 40 characters, and
each string must be enclosed in quotes.
Warning: When you use the CVALS= option, the variable
created in the output data set has a length equal to
the length of the longest string given as a value;
shorter strings are padded with trailing blanks.
For example, the values output for the first level of
a two-level factor with the following two different specifications
are not the same.
CVALS=('String 1' "String 2")
CVALS=('String 1' "A longer string")
The value output with the second specification
is 'String 1' followed by seven blanks.
In order to match two such values (for example, when merging
two plans), you must use the TRIM function in the DATA step
(refer to SAS Language Reference: Dictionary).
- ORDERED | RANDOM
specifies how values (those given with the NVALS=
or CVALS= option, or the default values) are associated with
the levels of a factor (the integers 1,2, ... ,n).
The default association type is ORDERED, for which the first
value specified is output for a factor level setting of 1, the
second value specified is output for a level of 2, and so on.
You can also specify an association type of RANDOM, for which
the levels are associated with the values in a random order.
Specifying RANDOM is useful for randomizing crossed experiments
(see the "Randomizing Designs" section).
The following statements give an example of using the OUTPUT statement
with only an OUT= data set and with both the NVALS= and CVALS=
factors a=6 ordered b=3;
output out=design a nvals=(10 to 60 by 10)
b cvals=('HSX' 'SB2' 'DNY');
The DESIGN data set contains two variables, a and b.
The values of the variable a are 10 when
factor a equals 1, 20 when factor a equals 2, and so on.
Values of the variable b are `HSX'
when factor b equals 1, `SB2' when factor b equals 2, and `DNY'
when factor b equals 3.
Factor-Value-Settings with OUT= and DATA= Data Sets
If you specify an input data set with DATA=, then
PROC PLAN assumes that each factor in the last plan
generated corresponds to a variable in the input set.
If the variable name is different from the name
of the factor to which it corresponds, the two
can be associated in the values specification by
- input-variable-name = factor-name
Then, the NVALS= or CVALS= specification can be used.
The values given by NVALS= or CVALS= specify the input values
as well as the output values for the corresponding variable.
Since the procedure assumes that the collection
of input factor values constitutes a plan position
description (see the "Output Data Sets" section),
the values must correspond to integers less than or equal to m,
the number of values selected for the associated factor.
If any input values do not correspond, then the collection does
not define a plan position, and the corresponding observation is
output without changing the values of any of the factor variables.
The following statements demonstrate the use of factor-value settings.
The input SAS data set a contains variables
Block and Plot, which are
renamed Day and Hour, respectively.
factors Day=7 Hour=6;
output data=a out=b
Block = Day cvals=('Mon' 'Tue' 'Wed' 'Thu'
'Fri' 'Sat' 'Sun' )
Plot = Hour;
For another example of using both a DATA= and OUT= data
set, see the the "Randomly Assigning Subjects to Treatments" section.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.