The POWER Procedure
- Overview
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Getting Started
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Syntax
PROC POWER Statement LOGISTIC Statement MULTREG Statement ONECORR Statement ONESAMPLEFREQ Statement ONESAMPLEMEANS Statement ONEWAYANOVA Statement PAIREDFREQ Statement PAIREDMEANS Statement PLOT Statement TWOSAMPLEFREQ Statement TWOSAMPLEMEANS Statement TWOSAMPLESURVIVAL Statement TWOSAMPLEWILCOXON Statement
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Details
Overview of Power Concepts Summary of Analyses Specifying Value Lists in Analysis Statements Sample Size Adjustment Options Error and Information Output Displayed Output ODS Table Names Computational Resources Computational Methods and Formulas ODS Graphics ODS Styles Suitable for Use with PROC POWER
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Examples
One-Way ANOVA The Sawtooth Power Function in Proportion Analyses Simple AB/BA Crossover Designs Noninferiority Test with Lognormal Data Multiple Regression and Correlation Comparing Two Survival Curves Confidence Interval Precision Customizing Plots Binary Logistic Regression with Independent Predictors Wilcoxon-Mann-Whitney Test
- References
Analyses in the TWOSAMPLESURVIVAL Statement
Rank Tests for Two Survival Curves (TEST=LOGRANK, TEST=GEHAN, TEST=TARONEWARE)
The method is from Lakatos (1988) and Cantor (1997, pp. 83–92).
Define the following notation:
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Each survival curve can be specified in one of several ways.
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For exponential curves:
a single point
on the curve median survival time
hazard rate
hazard ratio (for curve 2, with respect to curve 1)
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For piecewise linear curves with proportional hazards:
a set of points
(for curve 1) hazard ratio (for curve 2, with respect to curve 1)
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For arbitrary piecewise linear curves:
a set of points
A total of 
evenly spaced time points 
are used in calculations, where
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The hazard function is calculated for each survival curve at each time point. For an exponential curve, the (constant) hazard is given by one of the following, depending on the input parameterization:
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For a piecewise linear curve, define the following additional notation:
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The hazard is computed by using linear interpolation as follows:
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With proportional hazards, the hazard rate of group 2’s curve in terms of the hazard rate of group 1’s curve is
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Hazard function values 
for the loss curves are computed in an analogous way from 
.
The expected number at risk 
at time 
in group 
is calculated for each group and time points 
through 
, as follows:
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Define 
as the ratio of hazards and 
as the ratio of expected numbers at risk for time 
:
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The expected number of deaths in each subinterval is calculated as follows:
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The rank values are calculated as follows according to which test statistic is used:
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The distribution of the test statistic is approximated by 
where
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Note that 
can be factored out of the mean 
, and so it can be expressed equivalently as
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where 
is free of 
and
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The approximate power is
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Note that the upper and lower one-sided cases are expressed differently than in other analyses. This is because 
corresponds to a higher survival curve in group 1 and thus, by the convention used in PROC power for two-group analyses, the lower side.
For the one-sided cases, a closed-form inversion of the power equation yield an approximate total sample size
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For the two-sided case, the solution for is obtained by numerically inverting the power equation.
Accrual rates are converted to and from sample sizes according to the equation 
, where 
is the accrual rate for group .
Expected numbers of events—that is, deaths, whether observed or censored—are converted to and from sample sizes according to the equation
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where 
is the expected number of events in group . For an exponential curve, the equation simplifies to
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For a piecewise linear curve, first define 
as the number of time points in the following collection: 
, 
, and input time points for group strictly between and . Denote the ordered set of these points as 
. The survival function values 
and 
are calculated by linear interpolation between adjacent input time points if they do not coincide with any input time points. Then the equation for a piecewise linear curve simplifies to
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