
ALPHA=p

specifies the level of significance p for % 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.
You can override the default in each of these cases by specifying the ALPHA= option for each statement individually.

DATA=SASdataset

names the SAS data set used by the GLM procedure. By default, PROC GLM uses the most recently created SAS data set.

MANOVA

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.

MULTIPASS

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.

NAMELEN=n

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.

NOPRINT

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.

ORDER=DATA  FORMATTED  FREQ  INTERNAL

specifies the sort order for the levels of the classification variables (which are specified in the CLASS statement). This ordering determines which parameters in the model correspond to each level in the data, so the ORDER= option
can be useful when you specify the CONTRAST or ESTIMATE statement.
This option applies to the levels for all classification variables, except when you use the (default) ORDER=FORMATTED option
with numeric classification variables that have no explicit format. In that case, the levels of such variables are ordered
by their internal value.
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

By default, ORDER=FORMATTED. 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.

OUTSTAT=SASdataset

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 analysis.
See the section Output Data Sets for more information.

PLOTS <(globalplotoptions)> <=plotrequest <(options)>>
PLOTS <(globalplotoptions)> <=(plotrequest <(options)> <... plotrequest <(options)>>)>

controls the plots produced through ODS Graphics. When you specify only one plotrequest, you can omit the parentheses from around the plotrequest. For example:
PLOTS=NONE
PLOTS=(DIAGNOSTICS RESIDUALS)
PLOTS(UNPACK)=RESIDUALS
PLOT=MEANPLOT(CLBAND)
ODS Graphics must be enabled before plots can be requested. For example:
ods graphics on;
proc glm data=iron;
model loss=fe fe*fe;
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.
If ODS Graphics is enabled but you 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 oneway analysis of variance model, with just one CLASS variable, the GLM procedure produces a grouped box plot of the response values versus the CLASS levels. For an example of the box plot, see the section OneWay Layout with Means Comparisons in Chapter 26: The ANOVA Procedure.

If you specify a twoway analysis of variance model, with just two CLASS variables, the GLM procedure produces 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
twoway 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 produces 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 produces 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 produces 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 44.4.

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

If you specify a MEANS statement, the GLM procedure produces a grouped box plot of the response values versus the effect for which means are being
calculated.
The globalplotoptions include the following:

MAXPOINTS=NONE  number

specifies that plots with elements that require processing of more than number points be suppressed. The default is MAXPOINTS=5000. This limit is ignored if you specify MAXPOINTS=NONE.

ONLY

suppresses the default plots. Only plots specifically requested are displayed.

UNPACKPANEL
UNPACK

suppresses paneling. By default, multiple plots can appear in some output panels. Specify UNPACKPANEL to get each plot in
a separate panel. You can specify PLOTS(UNPACKPANEL) to just unpack the default plots. You can also specify UNPACKPANEL as
a suboption with DIAGNOSTICS and RESIDUALS.
The following individual plots and plot options are available. If you specify only one plot, then you can omit the parentheses.

ALL

produces all appropriate plots. You can specify other options with ALL; for example, to request all plots and unpack just
the residuals, specify: PLOTS=(ALL RESIDUALS(UNPACK)).

ANCOVAPLOT<(CLM CLI LIMITS)>

modifies the analysis of covariance plot produced by default when you have an analysis of covariance model, with one or two
CLASS variables and one continuous variable. By default the plot does not show confidence limits around the predicted values. The
PLOTS=ANCOVAPLOT(CLM) option adds limits for the expected predicted values, and PLOTS=ANCOVAPLOT(CLI) adds limits for new
predictions. Use PLOTS=ANCOVAPLOT(LIMITS) to add both kinds of limits.

ANOMPLOT

requests an analysis of means display, in which least squares means are compared against an average least squares mean (Ott
1967; Nelson 1982, 1991, 1993). LSmean ANOM plots are produced only if you also specify PDIFF=ANOM or ADJUST=NELSON in the LSMEANS statement, and in this case they are produced by default.

BOXPLOT<(NPANELPOS=n)>

modifies the plot produced by default for the model effect in a oneway analysis of variance model, or for an effect specified
in the MEANS statement. Suppose the effect has m levels. By default, or if you specify PLOTS=BOXPLOT(NPANELPOS=0), all m levels of the effect are displayed in a single plot. Specifying a nonzero value of n will result in P panels, where P is the integer part of . If , then the levels will be approximately balanced across the P panels; whereas if , precisely levels will be displayed on each panel except possibly the last.

CONTOURFIT<(OBS=obsoptions)>

modifies the contour fit plot produced by default when you have a model involving only two continuous predictors. The plot
displays a contour plot of the predicted surface overlaid with a scatter plot of the observed data. You can use the following
obsoptions to control how the observations are displayed:

GRADIENT

specifies that observations are displayed as circles colored by the observed response. The same color gradient is used to
display the fitted surface and the observations. Observations where the predicted response is close to the observed response
have similar colors: the greater the contrast between the color of an observation and the surface, the larger the residual
is at that point.

NONE

suppresses the observations.

OUTLINE

specifies that observations are displayed as circles with a border but with a completely transparent fill.

OUTLINEGRADIENT

is the same as OBS=GRADIENT except that a border is shown around each observation. This option is useful to identify the location
of observations where the residuals are small, since at these points the color of the observations and the color of the surface
are indistinguishable. OBS=OUTLINEGRADIENT is the default if you do not specify any obsoptions.

CONTROLPLOT

requests a display in which least squares means are compared against a reference level. LSmean control plots are produced
only when you specify PDIFF=CONTROL or ADJUST=DUNNETT in the LSMEANS statement, and in this case they are produced by default.

DIAGNOSTICS<(LABEL UNPACK)>

requests that a panel of summary diagnostics for the fit be displayed. The panel displays scatter plots of residuals, absolute
residuals, studentized residuals, and observed responses by predicted values; studentized residuals by leverage; Cook’s D by observation; a QQ plot of residuals; a residual histogram; and a residualfit spread plot. The LABEL option displays
labels on observations satisfying RSTUDENT , LEVERAGE , and on the Cook’s D plot, COOKSD , where n is the number of observations used in fitting the model, and p is the number of parameters in the model. The label is the first ID variable if the ID statement is specified; otherwise, it is the observation number. The UNPACK option unpanels the diagnostic display and produces
the series of individual plots that form the paneled display.

DIFFPLOT<(ABS NOABS CENTER NOLINES)>

modifies the plot produced by an LSMEANS statement with the PDIFF=ALL option (or just PDIFF, since ALL is the default argument). The ABS and NOABS options determine the positioning of the line segments in the plot.
When the ABS option is in effect, and this is the default, all line segments are shown on the same side of the reference line.
The NOABS option separates comparisons according to the sign of the difference. The CENTER option marks the center point for
each comparison. This point corresponds to the intersection of two least squares means. The NOLINES option suppresses the
display of the line segments that represent the confidence bounds for the differences of the least squares means. The NOLINES
option implies the CENTER option. The default is to draw line segments in the upper portion of the plot area without marking
the center point.

FITPLOT<(NOCLM NOCLI NOLIMITS)>

modifies the fit plot produced by default when you have a model with a single continuous predictor. By default the plot includes
confidence limits for both the expected predicted values and individual new predictions. The PLOTS=FITPLOT(NOCLM) option removes
the limits on the expected values and the PLOTS=FITPLOT(NOCLI) option removes the limits on new predictions. The PLOTS=FITPLOT(NOLIMITS)
option removes both kinds of confidence limits.

INTPLOT<(CLM CLI LIMITS)>

modifies the interaction plot produced by default when you have a twoway analysis of variance model, with just two CLASS variables. By default the plot does not show confidence limits around the predicted values. The PLOTS=INTPLOT(CLM) option
adds limits for the expected predicted values and PLOTS=INTPLOT(CLI) adds limits for new predictions. Use PLOTS=INTPLOT(LIMITS)
to add both kinds of limits.

MEANPLOT<(CL CLBAND CONNECT ASCENDING DESCENDING)>

modifies the grouped box plot produced by an MEANS statement. Upper and lower confidence limits are plotted when the CL option is used. When the CLBAND option is in effect,
confidence limits are shown as bands and the means are connected. By default, means are not joined by lines. You can achieve
that effect with the CONNECT option. Means are displayed in the same order as they appear in the “Means” table. You can change that order for plotting with the ASCENDING and DESCENDING options.

NONE

specifies that no graphics be displayed.

RESIDUALS<(SMOOTH UNPACK)>

requests that scatter plots of the residuals against each continuous covariate be displayed. The SMOOTH option overlays a
Loess smooth on each residual plot. Note that if a WEIGHT variable is specified, then it is not used to weight the smoother. See Chapter 57: The LOESS Procedure, for more information. The UNPACK option unpanels the residual display and produces a series of individual plots that form
the paneled display.