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The MULTTEST Procedure |

If a resampling-based adjusted *p*-value is requested, then
the simulation standard error is included as either sim_se
or stpsimse, depending upon whether single-step or
stepdown adjustments are requested. The simulation standard
errors are used to bound the true resampling-based adjusted
*p*-value. For example, if the resampling-based estimate
is 0.0312 and the simulation standard error is 0.00123, then
a 95% confidence interval for the true adjusted *p*-value
is , or 0.0288 to 0.0336.

Intermediate statistics used to calculate the *p*-values are also
written to the OUT= data set. The statistics are separated by the
_strat_ level. When _strat_ is reported as
missing, then the statistics refer to the pooled analysis over all
_strat_ levels. The *p*-values are provided only for the
pooled analyses and are therefore reported as missing for the
strata-specific statistics.

For the PETO test, an additional variable, _tstrat_, is included to indicate whether the stratum is an incidental occurrence stratum (_tstrat_=0) or a fatal occurrence stratum (_tstrat_=1).

The statistic _value_ is the per-strata contribution to the numerator of the overall test statistic. In the case of the MEAN test, this is the contrast function of the sample means multiplied by the total number of observations within the stratum. For the FT test, _value_ is the contrast function of the double-arcsine transformed proportions, again multiplied by the total number of observations within the stratum. For the CA and PETO tests, _value_ is the observed value of the trend statistic within that stratum.

When either PETO or CA is requested, the variable _exp_ is included; this variable contains the expected value of the trend statistic for the given stratum.

The statistic _se_ is the square root of the variance of the per-strata _value_ value for any of the tests.

For MEAN tests, the variable _nval_ is included. When
reported with an individual stratum level (that is, when the
_strat_ value is nonmissing), the value _nval_ refers to
the within-stratum sample size. For the combined analysis (that is,
the value of the _strat_ is missing), the value
_nval_ contains degrees of freedom of the *t*-distribution used
to compute the unadjusted *p*-value.

When the FISHER test is requested, the OUT= data set contains variables _xval_, _mval_, _yval_, and _nval_, which define observations and sample sizes in the two groups defined by the CONTRAST statement.

For example, the OUT= data set from the drug example in the "Getting Started" section is displayed in Figure 43.4.

Each new data set is randomly drawn from the original data set, either with (bootstrap) or without (permutation) replacement. The size of this data set is, thus, the number of observations in the original data set times the number of samples.

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