known.designs: Show the 'known' designs

View source: R/DesignHelpers.R

known.designsR Documentation

Show the 'known' designs


Returns the known study designs for which power and sample size can be calculated within this package.




This function is for informal purposes and used internally for obtaining characteristics of the designs used in calculation formulas.


Returns a data.frame with


number of the design


character string for identifying the design


degrees of freedom of the design


‘robust’ degrees of freedom of the design


step width in the iterative sample size estimation


so-called design constant in terms of total n


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.


The design string for higher order crossover designs is named as:
treatments x sequences x periods in case of replicate designs and
treatments x periods in case of crossover designs for more then 2 treatments with number of sequences equal number of treatments.

The df for the replicate crossover designs are those without carry-over in the model.
Chen et al. used models with carry-over, i.e., one df lower than here.

The design constant bk in case of design 2x2x4 is here bk=1.
Chen et al. used bk=1.1 due to carry-over in the model.

n is the total number of subjects for all designs implemented.
df2 = degrees of freedom for the so-called ‘robust’ analysis (aka Senn’s basic estimator).
These degrees of freedom are often also more appropriate in case of evaluation via a ‘true’ mixed model (e.g. the FDA’ for replicate designs).

The design 2x2x2r is the 2-treatment-2-sequence-2-period design with 2 repeated targets determined in each period (sequences TT|RR or RR|TT) described by Liu. Implemented are the characteristics of this design for the evaluation via assuming no S×F interaction and equal variabilities of Test and Reference.


D. Labes


Chen KW, Chow SC, Liu G. A Note on Sample Size Determination for Bioequivalence Studies with Higher-order Crossover Designs. J Pharmacokin Biopharm. 1997;25(6):753–65.

Senn S. Cross-over Trials in Clinical Research. Chichester: John Wiley & Sons; 2nd edition 2002.

U.S. Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research (CDER). Guidance for Industry. Statistical Approaches to Establishing Bioequivalence. January 2001. download

Liu J-p. Use of the Repeated Crossover design in Assessing Bioequivalence. Stat Med. 1995;14(9-10):1067–78.



PowerTOST documentation built on March 18, 2022, 5:47 p.m.