asypow.sig {asypow} | R Documentation |
Calculates the significance level of a test via likelihood ratio methods.
asypow.sig(asypow.obj, sample.size, power)
asypow.obj |
The object returned from asypow.noncent. |
sample.size |
The sample size of the test. |
power |
The power of the test. |
Returns the significance level of the test.
Cox, D.R. and Hinkley, D.V. (1974). Theoretical Statistics Chapman and Hall, London.
asypow.noncent
,
asypow.n
,
asypow.power
# Single Group Binomial Example: # Consider testing the null hypothesis that the binomial # probability is p = .2 when the actual probability is .4. # What significance level corresponding to a sample # size of 47 and power of .8? # 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 sig.binom <- asypow.sig(binom.object, 47, 0.8) print(sig.binom)