Better 0.95 or 0.90 [Power / Sample Size]
❝ ❝ In this case, why they assume GMR=1.10 instead of the "normal" 0.95/1.05.
❝
❝ This was […] a very rare case, but in General GMR would be taken as 0.95/1.05 as you said, but the power remains same as 95% to 99%
Similar ≠ same.
CV 0.20, GMR 1.10, target 80%, n 32 (power 81.01%), no dropouts expected
1e+05 simulated studies with “post hoc” power of
≥ target : 54.04%
≥ achieved : 51.57%
≥ 0.90 : 26.98%
[0.95, 0.99]: 10.41%
≥ 0.95 : 12.50%
CV 0.20, GMR 1.05, target 80%, n 18 (power 80.02%), no dropouts expected
1e+05 simulated studies with “post hoc” power of
≥ target : 48.45%
≥ achieved : 48.41%
≥ 0.90 : 25.26%
[0.95, 0.99]: 9.72%
≥ 0.95 : 12.92%
I still don’t understand what you wrote above:
❝ […] always it is coming in the interval 95 to 99 and some times 100
BTW, power curves are not symmetric in raw scale but in log-scale (see this post). If you are not – very – confident about the sign of ∆, I recommend to use GMR=1–∆ in order to be on the safe side. By this, power is preserved for GMR=1/(1–∆) as well. If you use GMR=1+∆, power for GMR=1–∆ will be insufficient:
cat(paste0("\u2206 with unknown sign: ", 100*delta, "%",
"\n based on GMR = 1 \u2013 \u2206 = ",
sprintf("%5.4f", 1-delta), " : n ",
plan.1[["Sample size"]],
"\n based on GMR = 1 + \u2206 = ",
sprintf("%5.4f", 1+delta), " : n ",
plan.2[["Sample size"]],
"\n based on GMR = 1 / (1 + \u2206) = ",
sprintf("%5.4f", 1/(1+delta)), ": n ",
plan.3[["Sample size"]],
"\n based on GMR = 1 / (1 \u2013 \u2206) = ",
sprintf("%5.4f", 1/(1-delta)), ": n ",
plan.4[["Sample size"]],
"\n\nTrue GMR = ", sprintf("%5.4f", 1-delta),
"\n n ", plan.2[["Sample size"]], ", power ",
sprintf("%4.2f%%", 100*power.TOST(CV=CV, theta0=1-delta,
n=plan.2[["Sample size"]])),
"\n n ", plan.1[["Sample size"]], ", power ",
sprintf("%4.2f%%", 100*plan.1[["Achieved power"]]),
"\nTrue GMR = ", sprintf("%5.4f", 1/(1+delta)),
"\n n ", plan.3[["Sample size"]], ", power ",
sprintf("%4.2f%%", 100*plan.3[["Achieved power"]]),
"\n n ", plan.1[["Sample size"]], ", power ",
sprintf("%4.2f%%", 100*power.TOST(CV=CV, theta0=1/(1+delta),
n=plan.1[["Sample size"]])),
"\nTrue GMR = ", sprintf("%5.4f", 1+delta),
"\n n ", plan.2[["Sample size"]], ", power ",
sprintf("%4.2f%%", 100*plan.2[["Achieved power"]]),
"\n n ", plan.1[["Sample size"]], ", power ",
sprintf("%4.2f%%", 100*power.TOST(CV=CV, theta0=1+delta,
n=plan.1[["Sample size"]])),
"\nTrue GMR = ", sprintf("%5.4f", 1/(1-delta)),
"\n n ", plan.4[["Sample size"]], ", power ",
sprintf("%4.2f%%", 100*plan.4[["Achieved power"]]),
"\n n ", plan.2[["Sample size"]], ", power ",
sprintf("%4.2f%%", 100*power.TOST(CV=CV, theta0=1/(1-delta),
n=plan.2[["Sample size"]])), "\n"))
∆ with unknown sign: 10%
based on GMR = 1 – ∆ = 0.9000 : n 38
based on GMR = 1 + ∆ = 1.1000 : n 32
based on GMR = 1 / (1 + ∆) = 0.9091: n 32
based on GMR = 1 / (1 – ∆) = 1.1111: n 38
True GMR = 0.9000
n 32, power 75.17%
n 38, power 81.55%
True GMR = 0.9091
n 32, power 81.01%
n 38, power 86.76%
True GMR = 1.1000
n 32, power 81.01%
n 38, power 86.76%
True GMR = 1.1111
n 38, power 81.55%
n 32, power 75.17%
In simple words, for ∆ 10% assume a GMR of 0.90 (which will preserve power for GMR up to 1.1111) and for ∆ 5% a GMR of 0.95 (covers up to 1.0526·).
If you assume a GMR of 1.10 power will be preserved only down to 0.9090 and with 1.05 down to 0.9524 – not to 0.90 or 0.95 as many probably expect.
Dif-tor heh smusma 🖖🏼 Довге життя Україна!
Helmut Schütz
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Complete thread:
- Power is getting high kms.srinivas 2017-12-26 07:39 [Power / Sample Size]
- Power is getting high? d_labes 2017-12-26 12:08
- Stop estimating post hoc power! Helmut 2017-12-26 12:22
- Stop estimating post hoc power! kms.srinivas 2017-12-26 13:00
- Stop estimating post hoc power! ElMaestro 2017-12-26 14:11
- Simulations Helmut 2017-12-26 15:51
- Simulations BE-proff 2017-12-27 06:53
- Simulations ElMaestro 2017-12-27 07:25
- Simulations Yura 2017-12-27 08:23
- Simulations kms.srinivas 2017-12-27 09:11
- Simulations Yura 2017-12-27 10:07
- α and 1–β Helmut 2017-12-27 12:57
- α and 1–β Yura 2017-12-27 13:33
- α and 1–β Helmut 2017-12-27 14:31
- α and 1–β Yura 2017-12-28 06:50
- Educate the IEC and regulators Helmut 2017-12-28 11:30
- α and 1–β Yura 2017-12-28 06:50
- α and 1–β Helmut 2017-12-27 14:31
- α and 1–β Yura 2017-12-27 13:33
- α and 1–β Helmut 2017-12-27 12:57
- “Forced BE” 101 Helmut 2017-12-27 12:23
- “Forced BE” 101 kms.srinivas 2017-12-27 12:41
- Would you be so kind answering our questions? Helmut 2017-12-27 13:02
- Would you be so kind answering our questions? kms.srinivas 2017-12-28 05:53
- Yes, but why? Helmut 2017-12-28 11:47
- Yes, but why? DavidManteigas 2017-12-28 16:59
- Optimists and pessimists Helmut 2017-12-28 17:33
- "normal" GMR setting d_labes 2017-12-28 18:57
- Example for discussion mittyri 2017-12-28 22:06
- Example for discussion Helmut 2017-12-28 22:33
- I prefer to play it safe Helmut 2017-12-28 22:10
- Example for discussion mittyri 2017-12-28 22:06
- "normal" GMR setting d_labes 2017-12-28 18:57
- Full ACK d_labes 2017-12-28 17:41
- About GMR 1.10 kms.srinivas 2017-12-29 13:20
- Better 0.95 or 0.90Helmut 2017-12-29 16:18
- Optimists and pessimists Helmut 2017-12-28 17:33
- Yes, but why? Yura 2017-12-29 13:46
- Buffon's needle Astea 2018-01-20 23:55
- Buffon's needle Oleg777 2018-10-09 22:48
- 0.95 or 1.05 Helmut 2018-10-10 13:41
- Buffon's needle Helmut 2018-10-10 12:46
- Buffon's needle Astea 2018-10-11 23:14
- School maths Helmut 2018-10-12 01:10
- School russian Astea 2018-10-12 12:41
- Offtop: Umschrift der westlichen Eigennamen auf Russisch mittyri 2018-10-12 23:25
- School maths Helmut 2018-10-12 01:10
- Buffon's needle Astea 2018-10-11 23:14
- Buffon's needle Oleg777 2018-10-09 22:48
- Yes, but why? DavidManteigas 2017-12-28 16:59
- Yes, but why? Helmut 2017-12-28 11:47
- EEU? mittyri 2017-12-28 21:52
- EEU? Yura 2017-12-29 13:41
- EEU - pharmacokinetic equation??? mittyri 2017-12-29 14:11
- EEU? Beholder 2018-01-16 15:10
- EEU? Yura 2017-12-29 13:41
- Would you be so kind answering our questions? kms.srinivas 2017-12-28 05:53
- Would you be so kind answering our questions? Helmut 2017-12-27 13:02
- “Forced BE” 101 kms.srinivas 2017-12-27 12:41
- Simulations Yura 2017-12-27 10:07
- Simulations kms.srinivas 2017-12-27 09:11
- Simulations xtianbadillo 2018-01-18 22:22
- Simulations BE-proff 2017-12-27 06:53
- Stop estimating post hoc power! kms.srinivas 2017-12-26 13:00
- Numbers don't lie ElMaestro 2017-12-28 20:13