conditional.power: Conditional power for sequential tests.

Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/conditional.power.R

Description

Compute conditional power for Sequential tests in clinical trials.

Usage

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  conditional.power(tk=0, theta=0.5, sig.level=0.025, power = 0.8, tm = 0.5)

# Conditional power for survival analysis
#
  cpower.surv(hrk = 1.0, HR = 0.7, sig.level = 0.025, power = 0.8, tm = 0.5) 
#
#
# Conditional power for t-test
#
  cpower.tt(muk = 0.0, mu = 0.7, sig.level = 0.025, power = 0.8, 
      tm = 0.5, sigma = 1.0, cc.ratio = 1) 
#
#

Arguments

cc.ratio

Control / case ratio, default is 1

sig.level

Significance level (Type I error probability)

power

Power of test (1 minus Type II error probability)

HR

Target hazards ratio for survival outcome

mu

Target difference for continuous outcome

sigma

Standard error for continuous outcome

theta

Difference under althernative hypothesis

muk

Difference in mean for the k^th interim analysis

tk

Test statistics Tk for the k^th interim analysis

hrk

Observed harzards ratio for the k^th interim analysis

tm

Time of the k^th test (percentage of information)

Details

Calculate conditional power for sequential tests in clinical trials to provide information on whether or not to futile a study. The algorithm is based on methods by Jennison and Turnbull (2000) Chapter 10, page 207-220.

Value

Object of class 'power.htest', a list of the arguments (including the computed one) augmented with 'method' and 'note' elements.

case.control

A vector for number of cases and controls

n.total

Total number of sample size for the study

cpower.low

Lower conditional power for one-sided futility analysis

cpower.up

Upper conditional power for one-sided futility analysis

cpower

Conditional power for two-sided test

Power

Power of the test

I.max

Maximum information at the final analysis

zk

Standardized test statistics Zk at the k^th interim analysis

time

Time of the k^th interim analysis

Note

'uniroot' is used to solve power equation for unknowns, so you may see errors from it, notably about inability to bracket the root when invalid arguments are given.

Author(s)

Bingshu E. Chen (bingshu.chen@queensu.ca)

References

Jennison C. and Turnbull B. W. (2000). Group Sequential methods applications to clinical trials.

See Also

power.surv.test, power.t.test, pwr.2p.test

Examples

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# Example
conditional.power(tk=0, theta=0.5, sig.level=0.05, power = 0.8, tm = 0.5)

statapps/power.ctepd documentation built on July 30, 2020, 6:05 p.m.