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PROC MULTTEST Statement

PROC MULTTEST < options > ;

BONFERRONI

BON

specifies that the Bonferroni adjustments (number of tests × p-value) be computed for each test. These adjustments can be extremely conservative and should be viewed with caution. When exact tests are specified via the PERMUTATION= option in the TEST statement, the actual permutation distributions are used, resulting in a much less conservative version of this procedure (Westfall and Wolfinger 1997).

BOOTSTRAP

BOOT

specifies that the p-values be adjusted using the bootstrap method to resample vectors (Westfall and Young 1993). Resampling is performed with replacement and independently within levels of the STRATA variable. Continuous variables are mean-centered by default prior to resampling. The BOOTSTRAP option is not allowed with the PETO test for theoretical reasons.

If the PERMUTATION= option is used with the CA test, the exact permutation distribution is recomputed for each bootstrap sample. Caution: This can be very time-consuming. It is preferable to use permutation resampling when permutation base tests are used.

CENTER

requests that continuous variables be mean-centered prior to resampling. The default action is to mean-center for bootstrap resampling and not to mean-center for permutation resampling.

DATA=SAS-data-set

names the input SAS data set to be used by PROC MULTTEST. The default is to use the most recently created data set.

FDR

requests adjusted p-values using the method of Benjamini and Hochberg (1995). These p-values do not control the familywise error rate, but they do control the false discovery rate in some cases.

HOC

requests adjusted p-values using Hochberg's (1988) step-up Bonferroni method.

HOLM

is an alias for the STEPBON adjustment.

NOCENTER

requests that continuous variables not be mean-centered prior to resampling. The default action is to mean-center for bootstrap resampling and not to mean-center for permutation resampling.

NOPRINT

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

NOTABLES

suppresses display of the "Discrete Variable Tabulations" and "Continuous Variable Tabulations" tables.

NOZEROS

suppresses display of tables having zero occurrences for all CLASS levels.

NSAMPLE= number

N= number

specifies the number of resamples for use with the BOOTSTRAP and PERMUTATION options; it is assumed to be 20,000 by default. Large values of number (20,000 or more) are usually recommended for accuracy, but long execution times may result, particularly with large data sets.

ORDER=DATA  | FORMATTED | FREQ | INTERNAL

specifies the sorting order for the levels of the classification variable (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 the CONTRAST statements. The following table shows how PROC MULTTEST interprets values of the ORDER= option.

Value of ORDER=	Levels Sorted by
DATA	order of appearance in the input data set
FORMATTED	external formatted value
FREQ	descending frequency count; levels with the most observations come first in the order
INTERNAL	internal machine representation

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

OUT=SAS-data-set

names the output SAS data set containing variable names, contrast names, intermediate calculations, and all associated p-values.

OUTPERM=SAS-data-set

names the output SAS data set containing entire permutation distributions (upper-tail probabilities) for all tests when the PERMUTATION= option is used. Caution: This data set can be very large.

OUTSAMP=SAS-data-set

names the output SAS data set containing information from the resampled data sets when resampling is performed. Caution: This data set can be very large.

PDATA=SAS-data-set

names an input SAS data set containing the variable raw_p with observations that consist of raw p-values. The MULTTEST procedure adjusts the collection of raw p-values for multiplicity. The resampling-based adjustments cannot be performed using this type of data input, but all other adjustments can be performed. Output from PROC MULTTEST is contained in the OUT= data set when you specify the PDATA= input form, so you must use the OUT= option to obtain the results in this case.

PERMUTATION

PERM

specifies adjusted p-values in identical fashion as the BOOTSTRAP option, with the exception that PROC MULTTEST resamples without replacement rather than with replacement. Resampling is performed independently within levels of the STRATA variable. Continuous variables are not mean-centered prior to resampling. The PERMUTATION option is not allowed with the PETO test for theoretical reasons.

PVALS

requests that a summary table of raw and adjusted p-values be included.

SEED= number

S= number

specifies the initial seed for the random number generator used for resampling. The value for number must be a positive integer; the computer clock time is the default. For more details about seed values, refer to SAS Language Reference: Concepts.

SIDAK

SID

specifies that the Sidak adjustments be computed for each test. These adjustments take the form

1 - (1 - p)ⁿ

where p is the raw p-value and n is the number of tests. These are slightly less conservative than the Bonferroni adjustments, but they still should be viewed with caution. When exact tests are specified via the PERMUTATION= option in the TEST statement, the actual permutation distributions are used, resulting in a much less conservative version of this procedure (Westfall and Wolfinger 1997).

STEPBON

requests adjusted p-values using the stepdown Bonferroni method of Holm (1979).

STEPBOOT

requests that adjusted p-values be computed using bootstrap resampling as described under the BOOTSTRAP option, but in stepdown fashion.

STEPPERM

requests that adjusted p-values be computed using permutation resampling as described under the PERMUTATION option, but in stepdown fashion.

STEPSID

requests adjusted p-values using the Sidak method as described in the SIDAK option, but in stepdown fashion.

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