specifies the level of significance for % confidence intervals. The value must be between 0 and 1; the default value of results in 95% intervals. This value is used as the default confidence level for limits computed by the following options.

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 characters long, where 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 20, Using the Output Delivery System, for more information.

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 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. Before SAS 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= option.

By default, ORDER=FORMATTED. For FORMATTED and INTERNAL, the sort order is machine dependent.

For more information about sorting order, see the chapter on the SORT procedure in the Base 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, 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 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 analysis.

See the section Output Data Sets for more information.

controls the plots produced through ODS Graphics. When you specify only one plot request, you can omit the parentheses from around the plot request. For example:

   PLOTS=NONE
   PLOTS=(DIAGNOSTICS RESIDUALS)
   PLOTS(UNPACK)=RESIDUALS
   PLOT=MEANPLOT(CLBAND)

You must enable ODS Graphics before requesting plots, as in the following statements.

   ods graphics on;
   proc glm data=iron;
      model loss=fe fe*fe;
   run;
   ods graphics off;

For general information about ODS Graphics, see Chapter 21, Statistical Graphics Using ODS. If you have enabled ODS Graphics but do not specify the PLOTS= option, then PROC GLM produces a default set of plots, which might be different for different models, as discussed in the following.

• If you specify a one-way analysis of variance model, with just one CLASS variable, the GLM procedure will produce a grouped box plot of the response values versus the CLASS levels. For an example of the box plot, see the section One-Way Layout with Means Comparisons.

• If you specify a two-way analysis of variance model, with just two CLASS variables, the GLM procedure will produce an interaction plot of the response values, with horizontal position representing one CLASS variable and marker style representing the other; and with predicted response values connected by lines representing the two-way analysis. For an example of the interaction plot, see the section PROC GLM for Unbalanced ANOVA.

• If you specify a model with a single continuous predictor, the GLM procedure will produce a fit plot of the response values versus the covariate values, with a curve representing the fitted relationship and a band representing the confidence limits for individual mean values. For an example of the fit plot, see the section PROC GLM for Quadratic Least Squares Regression.

• If you specify a model with two continuous predictors and no CLASS variables, the GLM procedure will produce a contour fit plot, overlaying a scatter plot of the data and a contour plot of the predicted surface.

• If you specify an analysis of covariance model, with one or two CLASS variables and one continuous variable, the GLM procedure will produce an analysis of covariance plot of the response values versus the covariate values, with lines representing the fitted relationship within each classification level. For an example of the analysis of covariance plot, see Example 39.4.

• If you specify an LSMEANS statement with the PDIFF option, the GLM procedure will produce a plot appropriate for the type of LS-means comparison. For PDIFF=ALL (which is the default if you specify only PDIFF), the procedure produces a diffogram, which displays all pairwise LS-means differences and their significance. The display is also known as a “mean-mean scatter plot” (Hsu 1996). For PDIFF=CONTROL, the procedure produces a display of each noncontrol LS-mean compared to the control LS-mean, with two-sided confidence intervals for the comparison. For PDIFF=CONTROLL and PDIFF=CONTROLU a similar display is produced, but with one-sided confidence intervals. Finally, for the PDIFF=ANOM option, the procedure produces an "analysis of means" plot, comparing each LS-mean to the average LS-mean.

• If you specify a MEANS statement, the GLM procedure will produce a grouped box plot of the response values versus the effect for which means are being calculated.

The global plot options include the following:

The following individual plots and plot options are available. If you specify only one plot, then you can omit the parentheses.