PowerTOST: sampleN.NTID() [Power / Sample Size]
❝ Let me understand again by looking following framework,
❝ Following data is available with me,
❝ Target power : eg, 0.8, .85, 0.9, CwT,CwR,sigWT,SigWR,theta0,theta1,theta2.
Although you could give values of
theta1
and theta2
, for the FDA keep the defaults of 0.8
and 1.25
(i.e., don’t specify anything): Additionally to passing RSABE and the variance-comparison you must pass conventional ABE.❝ i want to estimate sample size for low to moderate NTID.
More examples are given there.
❝ Also to estimate sample size by assuming 30 & 40 % dropout rate.
See the two supportive functions in the section about dropouts in the named article.
❝ I have gone through the examples. Sometimes error comes as its beyond implied limit.
That’s possible if you specify a low or high
theta0
. Background: $$\eqalign{s_0&=0.1\tag{1}\\\theta_\text{s}&=\frac{\log_e(1/0.9)}{s_0}\approx1.053605\ldots\\
\left\{\theta_{\text{s}_1},\theta_{\text{s}_2}\right\}&=\exp(\mp\theta_\text{s}\cdot s_\text{wR}),
}$$ where \(\small{s_0}\) is the regulatory switching condition, \(\small{\theta_\text{s}}\) the regulatory constant, and finally \(\small{\left\{\theta_{\text{s}_1},\theta_{\text{s}_2}\right\}}\) are the implied limits. Say, you assume \(\small{CV_\text{wR}=0.1}\). Since $$s_\text{wR}=\sqrt{\log_e(CV_\text{wR}^2+1)}\tag{2}$$ and by using \(\small{(1)}\) you end up with $$\left\{\theta_{\text{s}_1},\theta_{\text{s}_2}\right\}=\left\{0.9002,1.1108\right\}.\tag{3}$$ In other words, for this \(\small{CV_\text{wR}}\) any
theta0
outside these limits cannot work. That’s by design:library(PowerTOST)
sampleN.NTID(CV = 0.1, theta0 = 0.90)
+++++++++++ FDA method for NTIDs ++++++++++++
Sample size estimation
---------------------------------------------
Study design: 2x2x4 (TRTR|RTRT)
log-transformed data (multiplicative model)
1e+05 studies for each step simulated.
alpha = 0.05, target power = 0.8
CVw(T) = 0.1, CVw(R) = 0.1
True ratio = 0.9
ABE limits = 0.8 ... 1.25
Implied scABEL = 0.9002 ... 1.1108
Regulatory settings: FDA
- Regulatory const. = 1.053605
- 'CVcap' = 0.2142
Error: theta0 outside implied scABE limits! No sample size estimable.
Would you want to estimate a sample size for conventional ABE with a T/R-ratio outside 80–125%? Try:
sampleN.TOST(CV = 0.1, theta0 = 0.7999) # any (!) CV, targetpower, design
For NTIDs the FDA requires stricter batch-release spec’s (±5% instead of the common ±10%). Therefore,
theta0 = 0.975
is the default of this function. I would not go below 0.95
unless the CV is relatively high (no scaling if \(\small{CV_\text{wR}\geq0.2142}\)).❝ Heteroscedasticity can be challenging for me as T>R.
Yes, you are not alone.
❝ Can you check and verify if i am using correct programming.
I can’t till you post an example which you consider problematic.
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Complete thread:
- Estimation of sample size for NIT using ISCV By R pharm07 2022-05-03 11:23
- Estimation of sample size for NTI using ISCV By R dshah 2022-05-03 13:04
- PowerTOST Helmut 2022-05-03 14:38
- PowerTOST pharm07 2022-05-04 08:08
- PowerTOST Helmut 2022-05-04 10:33
- PowerTOST pharm07 2022-05-04 14:54
- PowerTOST pharm07 2022-05-11 05:30
- PowerTOST: sampleN.NTID()Helmut 2022-05-11 13:19
- PowerTOST: sampleN.NTID() pharm07 2022-05-18 05:18
- sampleN.NTID(): Example Helmut 2022-05-18 14:30
- sampleN.NTID(): Example pharm07 2022-05-19 05:36
- sampleN.NTID(): Example Helmut 2022-05-18 14:30
- PowerTOST: sampleN.NTID() pharm07 2022-05-18 05:18
- PowerTOST: sampleN.NTID()Helmut 2022-05-11 13:19
- PowerTOST pharm07 2022-05-11 05:30
- PowerTOST pharm07 2022-05-04 14:54
- PowerTOST Helmut 2022-05-04 10:33
- PowerTOST pharm07 2022-05-04 08:08