## naive questions regarding new functions in Power2Stage [Two-Stage / GS Designs]

Hi Helmut,

sorry for naive questions raised from my hazelnut brain

1. I'm trying to compare the old function

with a new one

So the old function was nice since the user can choose the method or specify 3 alphas.

In the new one I see the comment regarding alpha

What about alpha0 for method C? Is it deprecated?

2. Why did you decide to include CI futility rule by default?

3. Regarding your flowchart:

isn't it possible that we get some value lower than 4?

for example and after first stage CV=15%, CI=[0.7991897 1.0361745]:

4. Is it possible to update the docs attached to the library?

5. I was confused with "2stage" 'aliased' with "tsd" and was looking for differences some time

Are there any reasons to double that functions?

PS:

regarding 3rd point:

I tried

oh, there's a default argument min.n2 = 4

OK, let's try to change that:

Why couldn't I select a smaller one?

sorry for naive questions raised from my hazelnut brain

1. I'm trying to compare the old function

`power.tsd(method = c("B", "C", "B0"), alpha0 = 0.05, alpha = c(0.0294, 0.0294), `

n1, GMR, CV, targetpower = 0.8, pmethod = c("nct", "exact", "shifted"),

usePE = FALSE, Nmax = Inf, min.n2 = 0, theta0, theta1, theta2,

npct = c(0.05, 0.5, 0.95), nsims, setseed = TRUE, details = FALSE)

with a new one

`power.tsd.in(alpha, weight, max.comb.test = TRUE, n1, CV, targetpower = 0.8,`

theta0, theta1, theta2, GMR, usePE = FALSE, min.n2 = 4, max.n = Inf,

fCpower = targetpower, fCrit = "CI", fClower, fCupper, fCNmax,

ssr.conditional = c("error_power", "error", "no"),

pmethod = c("nct", "exact", "shifted"), npct = c(0.05, 0.5, 0.95),

nsims, setseed = TRUE, details = FALSE)

So the old function was nice since the user can choose the method or specify 3 alphas.

In the new one I see the comment regarding alpha

*If one element is given, the overall one-sided significance level. If two elements are given, the adjusted one-sided alpha levels for stage 1 and stage 2, respectively.*

If missing, defaults to 0.05.If missing, defaults to 0.05.

What about alpha0 for method C? Is it deprecated?

2. Why did you decide to include CI futility rule by default?

3. Regarding your flowchart:

isn't it possible that we get some value lower than 4?

`power.tsd.in(CV=0.13, n1=12)`

<...>

p(BE) = 0.91149

p(BE) s1 = 0.83803

Studies in stage 2 = 9.71%

Distribution of n(total)

- mean (range) = 12.5 (12 ... 42)

- percentiles

5% 50% 95%

12 12 16

for example and after first stage CV=15%, CI=[0.7991897 1.0361745]:

`sampleN2.TOST(CV=0.15, n1=12)`

Design alpha CV theta0 theta1

2x2 0.0294 0.15 0.95 0.8

theta2 n1 Sample size

1.25 12 2

Achieved power Target power

0.82711 0.8

4. Is it possible to update the docs attached to the library?

5. I was confused with "2stage" 'aliased' with "tsd" and was looking for differences some time

Are there any reasons to double that functions?

PS:

regarding 3rd point:

I tried

`interim.tsd.in(GMR1=sqrt(0.7991897 * 1.0361745), CV1=0.15,n1=12, fCrit="No")`

TSD with 2x2 crossover

Inverse Normal approach

- maximum combination test with weights for stage 1 = 0.5 0.25

- significance levels (s1/s2) = 0.02635 0.02635

- critical values (s1/s2) = 1.93741 1.93741

- BE acceptance range = 0.8 ... 1.25

- Observed point estimate from stage 1 is not used for SSR

- with conditional error rates and conditional (estimated target) power

Interim analysis of first stage

- Derived key statistics:

z1 = 1.87734, z2 = 3.54417,

Repeated CI = (0.79604, 1.04028)

- No futility criterion met

- Test for BE not positive (not considering any futility rule)

- Calculated n2 = 4

- Decision: Continue to stage 2 with 4 subjects

oh, there's a default argument min.n2 = 4

OK, let's try to change that:

`> interim.tsd.in(GMR1=sqrt(0.7991897 * 1.0361745), CV1=0.15,n1=12, fCrit="No", min.n2 = 2)`

Error in interim.tsd.in(GMR1 = sqrt(0.7991897 * 1.0361745), CV1 = 0.15, :

min.n2 has to be at least 4.

Why couldn't I select a smaller one?

—

Kind regards,

Mittyri

Kind regards,

Mittyri

### Complete thread:

- Finally: Exact TSD methods for 2×2 crossover designs Helmut 2018-04-21 17:17
- Exact TSD methods: Example Helmut 2018-04-21 20:33
- Finally: Exact TSD methods for 2×2 crossover designs ElMaestro 2018-04-21 20:49
- Flow chart (without details) Helmut 2018-04-21 21:41
- naive questions regarding new functions in Power2Stagemittyri 2018-04-28 15:54
- Some answers Helmut 2018-04-28 17:29
- Some more "answers" d_labes 2018-04-29 21:11
- clarification regarding user Power2Stage guides mittyri 2018-04-30 13:41

- naive questions regarding new functions in Power2Stagemittyri 2018-04-28 15:54

- Flow chart (without details) Helmut 2018-04-21 21:41
- Technicality: Weigths for the inverse normal approach d_labes 2018-04-25 14:19
- Selection of w and w* Helmut 2018-04-26 09:51
- Selection of w and w* d_labes 2018-04-26 20:02
- Now what? w & w* examples d_labes 2018-05-09 13:53
- Now what? w & w* examples Ben 2018-06-10 20:12
- Now what? w & w* examples Helmut 2018-06-11 13:57
- Now what? w & w* examples Ben 2018-06-12 19:14

- a bug in interim.tsd.in()? mittyri 2018-06-11 23:27
- a bug in interim.tsd.in()? Ben 2018-06-12 19:32
- Nonbinding futility rule d_labes 2018-06-13 16:59
- Bad weather? Helmut 2018-06-13 19:23
- NLYW? d_labes 2018-06-14 10:18

- Nonbinding futility rule Ben 2018-06-13 20:26
- Nonbinding futility rule d_labes 2018-06-14 10:47
- Nonbinding futility rule Ben 2018-06-15 17:58
- Binding / Nonbinding futility rule - alpha control d_labes 2018-06-16 19:42
- Binding / Nonbinding futility rule - alpha control Ben 2019-03-30 09:52

- Binding / Nonbinding futility rule - alpha control d_labes 2018-06-16 19:42

- Nonbinding futility rule Ben 2018-06-15 17:58

- Nonbinding futility rule d_labes 2018-06-14 10:47

- Bad weather? Helmut 2018-06-13 19:23

- Nonbinding futility rule d_labes 2018-06-13 16:59

- a bug in interim.tsd.in()? Ben 2018-06-12 19:32

- Now what? w & w* examples Helmut 2018-06-11 13:57

- Now what? w & w* examples Ben 2018-06-10 20:12

- Selection of w and w* Helmut 2018-04-26 09:51