Syntax

The following statements are available in PROC ORTHOREG.

• PROC ORTHOREG < options > ;

  • MODEL dependent=independents < / option > ;

  • BY variables ;

  • CLASS variables < / option > ;

  • WEIGHT variable ;

The BY, CLASS, MODEL, and WEIGHT statements are described after the PROC ORTHOREG statement.

PROC ORTHOREG Statement

• PROC ORTHOREG < options > ;

The PROC ORTHOREG statement has the following options:

DATA= SAS-data-set

• specifies the input SAS data set to use. By default, the procedure uses the most recently created SAS data set. The data set specified cannot be a TYPE=CORR, TYPE=COV, or TYPE=SSCP data set.

NOPRINT

• suppresses the normal display of results. Note that this option temporarily disables the Output Delivery System (ODS); see Chapter 14, Using the Output Delivery System, for more information.

ORDER=DATA FORMATTED FREQ INTERNAL

• specifies the order in which you want the levels of the classification variables (specified in the CLASS statement) to be sorted. This ordering determines which parameters in the model correspond to each level in the data. Note that the ORDER= option applies to the levels for all classification variables. The exception is the default ORDER=FORMATTED for numeric variables for which you have supplied no explicit format. In this case, the levels are ordered by their internal 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 ORDER= option can take the following values.

  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
  INTERNAL	unformatted value

  If you omit the ORDER= option, PROC ORTHOREG orders by the external formatted value.

OUTEST= SAS-data-set

• produces an output data set containing the parameter estimates, the BY variables, and the special variables _TYPE_ (value PARMS ), _NAME_ (blank), _RMSE_ (root mean squared error), and Intercept .

SINGULAR= s

• specifies a singularity criterion ( s ‰ 0) for the inversion of the triangular matrix R . By default, SINGULAR=10E ˆ’ 12.

BY Statement

• BY variables ;

You can specify a BY statement with PROC ORTHOREG to obtain separate analyses on observations in groups defined by the BY variables. When a BY statement appears, the procedure expects the input data set to be sorted in order of the BY variables.

If your input data set is not sorted in ascending order, use one of the following alternatives:

• Sort the data using the SORT procedure with a similar BY statement.

• Specify the BY statement option NOTSORTED or DESCENDING in the BY statement for the ORTHOREG procedure. The NOTSORTED option does not mean that the data are unsorted but rather that the data are arranged in groups (according to values of the BY variables) and that these groups are not necessarily in alphabetical or increasing numeric order.

• Create an index on the BY variables using the DATASETS procedure (in base SAS software).

For more information on the BY statement, refer to the discussion in SAS Language Reference: Concepts . For more information on the DATASETS procedure, refer to the discussion in the SAS Procedures Guide .

CLASS Statement

• CLASS variables < / option > ;

The CLASS statement names the classification variables to be used in the model. Typical class variables are Treatment , Sex , Race , Group , and Replication . If you use the CLASS statement, it must appear before the MODEL statement.

By default, class levels are determined from the entire formatted values of the CLASS variables. Note that this represents a slight change from previous releases in the way in which class levels are determined. In releases prior to Version 9, class levels were determined using no more than the first 16 characters of the formatted values. If you wish to revert to this previous behavior you can use the TRUNCATE option on the CLASS statement. In any case, you can use formats to group values into levels. Refer to the discussion of the FORMAT procedure in the SAS Procedures Guide and the discussions for the FORMAT statement and SAS formats in SAS Language Reference: Dictionary .

You can specify the following option in the CLASS statement after a slash(/):

TRUNCATE

• specifies that class levels should be determined using only up to the first 16 characters of the formatted values of CLASS variables. When formatted values are longer than 16 characters, you can use this option in order to revert to the levels as determined in releases previous to Version 9.

MODEL Statement

• MODEL dependent=independents < / option > ;

The MODEL statement names the dependent variable and the independent effects. Only one MODEL statement is allowed. The specification of effects and the parameterization of the linear model is the same as in the GLM procedure; see Chapter 32, The GLM Procedure, for further details.

The following option can be used in the MODEL statement:

NOINT

• omits the intercept term from the model.

WEIGHT Statement

• WEIGHT variable ;

A WEIGHT statement names a variable in the input data set whose values are relative weights for a weighted least-squares regression. If the weight value is proportional to the reciprocal of the variance for each observation, the weighted estimates are the best linear unbiased estimates (BLUE). For a more complete description of the WEIGHT statement, see the WEIGHT Statement section on page 1782 in Chapter 32, The GLM Procedure. .