Returns the known study designs for which power and sample size
can be calculated within this package.
Usage
known.designs()
Arguments
Value
Returns a data.frame with
no= number of the design
design= character string for identifying the design
df= degrees of freedom of the design
df2= 'robust' degrees of freedom of the design
steps= step width in the iterative sample size estimation
bk= so-called design constant in terms of total n
bkni= design constant in terms of number of subjects in (sequence) groups
The design character string has to be used in the functions calls for power and sample size.
Details
This function is for informal purposes and will be used internal
for obtaining characteristics of the designs used in calculation formulas.
References
K.-W. Chen, S.-C. Chow and G. Liu
"A Note on Sample Size Determination for Bioequivalence Studies with
Higher-order Crossover Designs"
J. Pharmacokinetics and Biopharmaceutics, Vol. 25, No. 6, p753-765 (1997)
S. Senn
"Cross-over Trials in Clinical Research"
Second Edition, John Wiley & Sons, Chichester 2002
FDA Guidance for Industry.
"Statistical Approaches to Establishing Bioequivalence"
U.S. Department of Health and Human Services,
Food and Drug Administration,
Center for Drug Evaluation and Research (CDER). January 2001
Liu J-P
"Use of the Repeated Crossover design in Assessing Bioequivalence"
Stat. Med. Vol. 14, 1067-1078 (1995)