Oranges [Two-Stage / GS Designs]
Dear Helmut,
seems I have spoken Suaheli.
What I meant was:
You perform stage 1 with n1. Only if necessary you perform stage 2 with n2. Thus N(total) isn't always n1+n2 (=100 in your example).
Then the 'expected' total sample size aka 'mean' sample size aka ASN can be calculated via my formula given above.
If it is reasonable to calculate a mean for a variable with only 2 values is left to you. That's the reason why
Hope my English was now the better Suaheli
.
seems I have spoken Suaheli.
What I meant was:
You perform stage 1 with n1. Only if necessary you perform stage 2 with n2. Thus N(total) isn't always n1+n2 (=100 in your example).
Then the 'expected' total sample size aka 'mean' sample size aka ASN can be calculated via my formula given above.
If it is reasonable to calculate a mean for a variable with only 2 values is left to you. That's the reason why
power.2stage.GS()
dosn't give back components concerning the sample size 'distribution', unlike the other power.2stage.whatever()
functions.Hope my English was now the better Suaheli

—
Regards,
Detlew
Regards,
Detlew
Complete thread:
- Adaptive TSD vs. “classical” GSD Helmut 2015-11-27 19:05 [Two-Stage / GS Designs]
- Adaptive TSD vs. “classical” GSD ElMaestro 2015-11-27 19:54
- “classical” GSD - E[n] d_labes 2015-11-30 11:15
- Apples are pears by comparing the weight Helmut 2015-12-01 16:35
- Apples are pears by comparing the weight d_labes 2015-12-03 09:16
- Apples are pears by comparing the weight Helmut 2015-12-03 13:10
- Orangesd_labes 2015-12-03 13:56
- Apples are pears by comparing the weight Helmut 2015-12-03 13:10
- Apples are pears by comparing the weight d_labes 2015-12-03 09:16
- Apples are pears by comparing the weight Helmut 2015-12-01 16:35
- Adaptive TSD vs. “classical” GSD Ben 2015-12-02 19:27
- Adaptive TSD vs. “classical” GSD Helmut 2015-12-03 03:11
- “classical” GSD alpha's d_labes 2015-12-03 09:47
- N sufficiently large‽ Helmut 2015-12-03 14:56
- An other one with 0.0304 d_labes 2015-12-03 16:15
- An other one with 0.0304 Helmut 2015-12-03 16:26
- An other one with 0.0304 d_labes 2015-12-03 16:15
- N sufficiently large‽ Helmut 2015-12-03 14:56
- Adaptive TSD vs. “classical” GSD Ben 2016-01-10 12:43
- “classical” GSD alpha's d_labes 2015-12-03 09:47
- Adaptive TSD vs. “classical” GSD Helmut 2015-12-03 03:11