PROC GLM Statement
- PROC GLM < options > ;
The PROC GLM statement starts the GLM procedure.
You can specify the following options in the PROC GLM statement:
specifies the level of significance p for 100(1-p)% confidence intervals.
The value must be between 0 and 1; the default value of p=0.05 results
in 95% intervals. This value is used as the default confidence
level for limits computed by the following options.
|MODEL||CLI CLM CLPARM|
|OUTPUT||UCL= LCL= UCLM= LCLM=|
You can override the default in each of these cases by specifying
the ALPHA= option for each statement individually.
names the SAS data set used by the GLM procedure.
By default, PROC GLM uses the most recently created SAS data set.
requests the multivariate mode of
eliminating observations with missing values.
If any of the dependent variables have missing values, the
procedure eliminates that observation from the analysis.
The MANOVA option is useful if you use PROC GLM in interactive
mode and plan to perform a multivariate analysis.
requests that PROC GLM reread the input data set
when necessary, instead of writing the necessary
values of dependent variables to a utility file.
This option decreases disk space usage at the expense of
increased execution times, and is useful only in rare situations
where disk space is at an absolute premium.
specifies the length of effect names in tables and output data sets
to be n characters long,
where n is a value between 20 and 200 characters. The default length
is 20 characters.
suppresses the normal display of results.
The NOPRINT option is useful when you want only to create
one or more output data sets with the procedure.
Note that this option
temporarily disables the Output Delivery
System (ODS); see Chapter 15, "Using the Output Delivery System," for more information.
- ORDER=DATA | FORMATTED | FREQ | INTERNAL
specifies the sorting order for the levels of all
classification variables (specified in the CLASS statement).
This ordering determines which parameters in the model
correspond to each level in the data, so the ORDER= option
may be useful when you use CONTRAST or ESTIMATE statements.
Note that the ORDER= option applies to the levels for all
The exception is ORDER=FORMATTED (the default) for numeric variables
for which you have supplied no explicit format
(that is, for which there is no corresponding FORMAT statement in the
current PROC GLM run or in the DATA step that created the data set).
In this case, the
levels are ordered by their internal (numeric) value. Note that this
represents a change from previous releases for how class levels are
ordered. In releases previous to Version 8, numeric class levels with
no explicit format were ordered by their BEST12. formatted values, and
in order to revert to the previous ordering you can specify this
format explicitly for the affected classification variables. The
change was implemented because the former default behavior for
ORDER=FORMATTED often resulted in levels not being ordered
numerically and usually required the user to intervene with an
explicit format or ORDER=INTERNAL to get the more natural ordering.
The following table shows how PROC GLM interprets values of the ORDER=
Value of ORDER=
Levels Sorted By
|DATA||order of appearance in the input data set|
|FORMATTED||external formatted value, except for numeric|
| ||variables with no explicit format, which are|
| ||sorted by their unformatted (internal) value|
|FREQ||descending frequency count; levels with the|
| ||most observations come first in the order|
By default, ORDER=FORMATTED.
For FORMATTED and INTERNAL, the sort order is machine dependent.
For more information on sorting order, see the chapter on
the SORT procedure in the SAS Procedures Guide,
and the discussion of BY-group processing in
SAS Language Reference: Concepts.
names an output data set that contains sums of
squares, degrees of freedom, F statistics, and
probability levels for each effect in the model,
as well as for each CONTRAST that uses the overall residual or error
mean square (MSE)
as the denominator in constructing the F statistic.
If you use the CANONICAL option in the MANOVA statement
and do not use an M= specification in the MANOVA statement,
the data set also contains results of the canonical
See the section "Output Data Sets" for more information.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.