## Probability of Success in BE studies [Design Issues]

❝ Recently I was asked to give Probability of success for a proposed BE study, My thinking is Target study power (usually 80%) is POS with additional correction factor due to the variability during study conduct applied to this target power, is my understanding correct?

*prior*information. Let’s start with a conventional sample size estimation based purely on assumptions.

`library(PowerTOST)`

CV <- 0.25

theta0 <- 0.95

target <- 0.80

sampleN.TOST(CV = CV, theta0 = theta0, design = "2x2", targetpower = target, details = FALSE)

+++++++++++ Equivalence test - TOST +++++++++++

Sample size estimation

-----------------------------------------------

Study design: 2x2 crossover

log-transformed data (multiplicative model)

alpha = 0.05, target power = 0.8

BE margins = 0.8 ... 1.25

True ratio = 0.95, CV = 0.25

Sample size (total)

n power

28 0.807439

`m <- 24 # sample size of prior study`

`expsampleN.TOST(CV = CV, theta0 = theta0, design = "2x2", targetpower = target,`

prior.parm = list(m = m, design = "2x2"), prior.type = "CV", details = FALSE)

++++++++++++ Equivalence test - TOST ++++++++++++

Sample size est. with uncertain CV

-------------------------------------------------

Study design: 2x2 crossover

log-transformed data (multiplicative model)

alpha = 0.05, target power = 0.8

BE margins = 0.8 ... 1.25

Ratio = 0.95

CV = 0.25 with 22 df

Sample size (ntotal)

n exp. power

32 0.822645

`expsampleN.TOST(CV = CV, theta0 = theta0, design = "2x2", targetpower = target,`

prior.parm = list(m = m, design = "2x2"), prior.type = "theta0", details = FALSE)

++++++++++++ Equivalence test - TOST ++++++++++++

Sample size est. with uncertain theta0

-------------------------------------------------

Study design: 2x2 crossover

log-transformed data (multiplicative model)

alpha = 0.05, target power = 0.8

BE margins = 0.8 ... 1.25

Ratio = 0.95

CV = 0.25

Sample size (ntotal)

n exp. power

44 0.810063

`expsampleN.TOST(CV = CV, theta0 = theta0, design = "2x2", targetpower = target,`

prior.parm = list(m = m, design = "2x2"), prior.type = "both", details = FALSE)

++++++++++++ Equivalence test - TOST ++++++++++++

Sample size est. with uncertain CV and theta0

-------------------------------------------------

Study design: 2x2 crossover

log-transformed data (multiplicative model)

alpha = 0.05, target power = 0.8

BE margins = 0.8 ... 1.25

Ratio = 0.95 with 22 df

CV = 0.25 with 22 df

Sample size (ntotal)

n exp. power

48 0.801190

*Dif-tor heh smusma*🖖🏼 Довге життя Україна!

_{}

Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮

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### Complete thread:

- Probability of Success in BE studies Achievwin 2024-05-03 13:43 [Design Issues]
- Probability of Success in BE studiesHelmut 2024-05-03 14:15
- Probability of Success in BE studies Achievwin 2024-05-06 14:49
- Probability of Success in BE studies d_labes 2024-05-06 15:16
- Probability of Success in BE studies Achievwin 2024-05-06 15:31

- Assumptions (plural) Helmut 2024-05-06 15:31
- Assumptions (plural) Achievwin 2024-05-06 15:51

- Probability of Success in BE studies d_labes 2024-05-06 15:16

- Probability of Success in BE studies Achievwin 2024-05-06 14:49

- Probability of Success in BE studiesHelmut 2024-05-03 14:15