Here is the design of a clinical trial:

Official Title: Electric Pace-pitched Hearing Achieves Natural Tonotopy

Included conditions:
- Deafness

Study Armgroups:
- {'label': 'Imaged based fitting', 'type': 'EXPERIMENTAL', 'description': 'Mapping of the electrical input of the cochlear implant will be based on an individualized natural frequency alignment as estimated with imaging methods.', 'interventionNames': ['Device: Imaged based fitting']}
- {'label': 'Clinical routine', 'type': 'NO_INTERVENTION', 'description': 'Mapping of the electrical input of the cochlear implant will be based on a one-size-fits-all, as is part of clinical routine.'}

Interventions:
- {'type': 'DEVICE', 'name': 'Imaged based fitting', 'description': 'Mapping of the electrical input of the cochlear implant will be based on an individualized natural frequency alignment as estimated with imaging methods.', 'armGroupLabels': ['Imaged based fitting']}

Primary Outcomes:
- {'measure': 'Speech understanding in quiet with cochlear implant', 'description': 'Speech understanding with CI in quiet measured with the Dutch Consonant Nucleus Consonant (CNC) test.', 'timeFrame': 'During the first 12 months of CI rehabilitation'}
- {'measure': 'Speech understanding in quiet with cochlear implant', 'description': 'Speech understanding with CI in quiet will be measured with the Dutch Matrix sentence test.', 'timeFrame': 'During the first 12 months of CI rehabilitation'}
- {'measure': 'Speech understanding in noise with cochlear implant', 'description': 'Speech understanding with CI in noise will be measured with the Dutch Matrix sentence test.', 'timeFrame': 'During the first 12 months of CI rehabilitation'}
- {'measure': 'Patient preference', 'description': 'At every fitting session, patients will be asked to rate their satisfaction with either the control or experimental program on a 10-point Visual Analog Sscale (1 dissatisfied - 10 very satisfied).', 'timeFrame': 'During the first 12 months of CI rehabilitation'}

Please estimate the sample size based on the assumption: 
Alpha range is 0.01-0.08, power is 0.08, and type 1 error is 0.05.
Sample size
        Complementary to the new study design for clinical trials presented in this paper, thought has also been given to a different method for a priori calculation of sample size and power. Instead of calculating the estimated number of participants needed for a given research study, one could also work the other way around. After all, many clinical trials depend on the supply of patients within a selective pool and do not have any additional recruiting possibilities. This study, which is no exception to that point, will aim to include a minimum sample of 20 participants during an inclusion period of 18â24âmonths. A maximum of 30 participants will be included if recruitment is prosperous.
        Sample size calculation is usually based on the primary study outcome, which in this study is the difference in CNC word recognition (test-retest at 65âdB SPL) between the experimental and standard CI setting after 6âmonths of rehabilitation. Using the concept of effect size as interpreted by Cohenâs d [64, 65], the following formula could be used to calculate sample size for a paired t test:
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				\begin{document}$$ \mathrm{N}=2+\left({\left({\mathrm{Z}}_{1-\upalpha /2}+{\mathrm{Z}}_{1-\upbeta}\right)}^2/{\mathrm{d}}^2\right) $$\end{document}N=2+Z1âÎ±/2+Z1âÎ²2/d2where Nâ=âsample size, Î±â=âtype 1 error, Î²â=âtype 2 error, dâ=âeffect size.
        Given the idea of a restricted sample size, it can be argued that it is more valuable to rearrange this formula as to calculate effect size.
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				\begin{document}$$ \mathrm{d}=\surd \left(2+\left({\left({\mathrm{Z}}_{1-\upalpha /2}+{\mathrm{Z}}_{1-\upbeta}\right)}^2\right)/\mathrm{N}\right) $$\end{document}d=â2+Z1âÎ±/2+Z1âÎ²2/N
        As a result, different outcomes in effect size can be calculated with a sample size range of 20â30 participants, an alpha range of 0.01â0.08 and a given power of 0.08. When considering a type 1 error of 0.05 and a sample size of 20, an effect size of 0.66 or larger can be detected. If 30 study participants are recruited and the alpha level is kept similar, the resulting detectable effect size is at least 0.53.