asypow.power {asypow} | R Documentation |
Calculates the power of a test via likelihood ratio methods.
asypow.power(asypow.obj, sample.size, significance)
asypow.obj |
The object returned from asypow.noncent. |
sample.size |
The sample size of the study. |
significance |
The significance level of the test. |
Returns the power of the test.
Cox, D.R. and Hinkley, D.V. (1974). Theoretical Statistics Chapman and Hall, London.
asypow.noncent
,
asypow.n
,
asypow.sig
# Single Group Binomial Example: # Consider testing the null hypothesis that the binomial # probability is p = .2 with a sample size of 47 and # signficance level of 0.05. What is the power of the # test if p is actually .4? # Step 1: Find the information matrix info.binom <- info.binomial.kgroup(.4) # Step 2: Create the constraints matrix constraints <- c(1, 1, .2) # Step 3: Find the noncentrality parameter and # degrees of freedom for the test binom.object <- asypow.noncent(.4, info.binom, constraints) # Step 4: Compute the power of a test with # sample size of 47 and a significance level 0.05 power.binom <- asypow.power(binom.object, 47, 0.05) print(power.binom)