Table 2.

Sample sizes based on exact and approximate approaches to achieve a power of |$80\%$| for |$\theta=0.8$| and |$0.75$|⁠, |$\alpha=0.025$| and keeping |$\lambda_R=21$| and |$\lambda_P=7$| under three different allocations. The simulated power (⁠|$ \hat{\phi} $|⁠) and estimated average type-I error (⁠|$ \hat{\alpha} $|⁠) for exact Bayesian approach under non-informative Gamma prior are also reported to show that calculated sample size is adequate to guarantee |$80\%$| power except for minor numerical fluctuation. Note, Frequentist type-I error is always strictly maintained at |$\alpha= 0.025$| by equation 4.1.

Frequentist normalApproximate BayesianExact Bayesian
|$E$||$R$||$P$||$\theta$||$\lambda_{E}$||$n_{P}$||$N$||$ \hat{\phi} $||$n_{P}$||$N$||$ \hat{\phi} $||$n_{P}$||$N$||$ \hat{\phi} $||$ \hat{\alpha} $|
   20.0792370.802782340.801792370.8020.0215
    19.71133390.8021123360.7981123360.8080.0222
   0.8019.41765280.7901755250.7951755250.7960.0225
    19.13129360.7953109300.7973029060.7890.0229
111 18.870021000.80369720910.79968520550.8020.0224
   20.0391170.810381140.813381140.8070.0173
    19.7501500.806481440.798481440.7860.0208
   0.7519.4661980.805651950.804651950.8040.0217
    19.1932790.803912730.804882640.7900.0185
    18.81404200.8011384140.8061333990.7870.0184
   20.0402000.805402000.808371850.7940.0219
    19.7572850.801572850.803522600.7980.0208
   0.8019.4894450.799894450.802814050.7830.0217
    19.11587900.7981577850.8001537650.8050.0193
221 18.835317650.80435217600.80235117550.7970.0189
   20.0201000.81319950.80018900.8210.0210
    19.7261300.816251250.809241200.8110.0201
   0.7519.4341700.808331650.801331650.8150.0181
    19.1482400.813462300.801452250.8310.0181
    18.8723600.808703500.804643200.8100.0180
   20.0331980.819321920.813311860.7950.0216
    19.7472820.804462760.799442640.8050.0210
   0.8019.4724320.798714260.796714260.7860.0199
    19.11287680.8031277620.7991257500.7950.0205
321 18.828717220.80028417040.79727716620.7820.0209
   20.016960.81415900.79915900.8020.0225
    19.7211260.821201200.813181080.7870.0201
   0.7519.4271620.799271620.809261560.8020.0216
    19.1382280.807372220.804372220.7960.0193
    18.8583480.807563360.800543240.8110.0188
Frequentist normalApproximate BayesianExact Bayesian
|$E$||$R$||$P$||$\theta$||$\lambda_{E}$||$n_{P}$||$N$||$ \hat{\phi} $||$n_{P}$||$N$||$ \hat{\phi} $||$n_{P}$||$N$||$ \hat{\phi} $||$ \hat{\alpha} $|
   20.0792370.802782340.801792370.8020.0215
    19.71133390.8021123360.7981123360.8080.0222
   0.8019.41765280.7901755250.7951755250.7960.0225
    19.13129360.7953109300.7973029060.7890.0229
111 18.870021000.80369720910.79968520550.8020.0224
   20.0391170.810381140.813381140.8070.0173
    19.7501500.806481440.798481440.7860.0208
   0.7519.4661980.805651950.804651950.8040.0217
    19.1932790.803912730.804882640.7900.0185
    18.81404200.8011384140.8061333990.7870.0184
   20.0402000.805402000.808371850.7940.0219
    19.7572850.801572850.803522600.7980.0208
   0.8019.4894450.799894450.802814050.7830.0217
    19.11587900.7981577850.8001537650.8050.0193
221 18.835317650.80435217600.80235117550.7970.0189
   20.0201000.81319950.80018900.8210.0210
    19.7261300.816251250.809241200.8110.0201
   0.7519.4341700.808331650.801331650.8150.0181
    19.1482400.813462300.801452250.8310.0181
    18.8723600.808703500.804643200.8100.0180
   20.0331980.819321920.813311860.7950.0216
    19.7472820.804462760.799442640.8050.0210
   0.8019.4724320.798714260.796714260.7860.0199
    19.11287680.8031277620.7991257500.7950.0205
321 18.828717220.80028417040.79727716620.7820.0209
   20.016960.81415900.79915900.8020.0225
    19.7211260.821201200.813181080.7870.0201
   0.7519.4271620.799271620.809261560.8020.0216
    19.1382280.807372220.804372220.7960.0193
    18.8583480.807563360.800543240.8110.0188
Table 2.

Sample sizes based on exact and approximate approaches to achieve a power of |$80\%$| for |$\theta=0.8$| and |$0.75$|⁠, |$\alpha=0.025$| and keeping |$\lambda_R=21$| and |$\lambda_P=7$| under three different allocations. The simulated power (⁠|$ \hat{\phi} $|⁠) and estimated average type-I error (⁠|$ \hat{\alpha} $|⁠) for exact Bayesian approach under non-informative Gamma prior are also reported to show that calculated sample size is adequate to guarantee |$80\%$| power except for minor numerical fluctuation. Note, Frequentist type-I error is always strictly maintained at |$\alpha= 0.025$| by equation 4.1.

Frequentist normalApproximate BayesianExact Bayesian
|$E$||$R$||$P$||$\theta$||$\lambda_{E}$||$n_{P}$||$N$||$ \hat{\phi} $||$n_{P}$||$N$||$ \hat{\phi} $||$n_{P}$||$N$||$ \hat{\phi} $||$ \hat{\alpha} $|
   20.0792370.802782340.801792370.8020.0215
    19.71133390.8021123360.7981123360.8080.0222
   0.8019.41765280.7901755250.7951755250.7960.0225
    19.13129360.7953109300.7973029060.7890.0229
111 18.870021000.80369720910.79968520550.8020.0224
   20.0391170.810381140.813381140.8070.0173
    19.7501500.806481440.798481440.7860.0208
   0.7519.4661980.805651950.804651950.8040.0217
    19.1932790.803912730.804882640.7900.0185
    18.81404200.8011384140.8061333990.7870.0184
   20.0402000.805402000.808371850.7940.0219
    19.7572850.801572850.803522600.7980.0208
   0.8019.4894450.799894450.802814050.7830.0217
    19.11587900.7981577850.8001537650.8050.0193
221 18.835317650.80435217600.80235117550.7970.0189
   20.0201000.81319950.80018900.8210.0210
    19.7261300.816251250.809241200.8110.0201
   0.7519.4341700.808331650.801331650.8150.0181
    19.1482400.813462300.801452250.8310.0181
    18.8723600.808703500.804643200.8100.0180
   20.0331980.819321920.813311860.7950.0216
    19.7472820.804462760.799442640.8050.0210
   0.8019.4724320.798714260.796714260.7860.0199
    19.11287680.8031277620.7991257500.7950.0205
321 18.828717220.80028417040.79727716620.7820.0209
   20.016960.81415900.79915900.8020.0225
    19.7211260.821201200.813181080.7870.0201
   0.7519.4271620.799271620.809261560.8020.0216
    19.1382280.807372220.804372220.7960.0193
    18.8583480.807563360.800543240.8110.0188
Frequentist normalApproximate BayesianExact Bayesian
|$E$||$R$||$P$||$\theta$||$\lambda_{E}$||$n_{P}$||$N$||$ \hat{\phi} $||$n_{P}$||$N$||$ \hat{\phi} $||$n_{P}$||$N$||$ \hat{\phi} $||$ \hat{\alpha} $|
   20.0792370.802782340.801792370.8020.0215
    19.71133390.8021123360.7981123360.8080.0222
   0.8019.41765280.7901755250.7951755250.7960.0225
    19.13129360.7953109300.7973029060.7890.0229
111 18.870021000.80369720910.79968520550.8020.0224
   20.0391170.810381140.813381140.8070.0173
    19.7501500.806481440.798481440.7860.0208
   0.7519.4661980.805651950.804651950.8040.0217
    19.1932790.803912730.804882640.7900.0185
    18.81404200.8011384140.8061333990.7870.0184
   20.0402000.805402000.808371850.7940.0219
    19.7572850.801572850.803522600.7980.0208
   0.8019.4894450.799894450.802814050.7830.0217
    19.11587900.7981577850.8001537650.8050.0193
221 18.835317650.80435217600.80235117550.7970.0189
   20.0201000.81319950.80018900.8210.0210
    19.7261300.816251250.809241200.8110.0201
   0.7519.4341700.808331650.801331650.8150.0181
    19.1482400.813462300.801452250.8310.0181
    18.8723600.808703500.804643200.8100.0180
   20.0331980.819321920.813311860.7950.0216
    19.7472820.804462760.799442640.8050.0210
   0.8019.4724320.798714260.796714260.7860.0199
    19.11287680.8031277620.7991257500.7950.0205
321 18.828717220.80028417040.79727716620.7820.0209
   20.016960.81415900.79915900.8020.0225
    19.7211260.821201200.813181080.7870.0201
   0.7519.4271620.799271620.809261560.8020.0216
    19.1382280.807372220.804372220.7960.0193
    18.8583480.807563360.800543240.8110.0188
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