6533b820fe1ef96bd127a37b
RESEARCH PRODUCT
Estimators and confidence intervals of f2 using bootstrap methodology for the comparison of dissolution profiles
Alfredo García-arietaZhengguo XuMatilde Merino-sanjuánVictor Mangas-sanjuansubject
PercentileSimilarity (network science)Sample size determinationStatisticsStatistical inferenceEstimatorHealth InformaticsPoint estimationExpected valueSoftwareConfidence intervalComputer Science ApplicationsMathematicsdescription
Abstract Background and objectives: The most widely used method to compare dissolution profiles is the similarity factor f 2 . When this method is not applicable, the confidence interval of f 2 using bootstrap methodology has been recommended instead. As neither details of the estimator nor the types of confidence intervals are described in the guidelines, the suitability of five estimators and fourteen types of confidence intervals were investigated in this study by simulation. Methods: One million individual dissolution profiles were simulated for the reference and test populations with predefined target population f 2 values, where random samples of different sizes were drawn without replacement. From each pair of random samples, five f 2 estimators were calculated, and fourteen types of confidence intervals were obtained using 5000 bootstrap samples. The whole process was repeated 10000 times and the percentage of the similarity conclusions was measured. In addition, the uncertainty associated with the current practice of using f ^ 2 point estimate alone for the statistical inference was evaluated. Results: When combined with different types of confidence intervals, the estimated f 2 ( f ^ 2 ), the bias-corrected f 2 ( f ^ 2 , bc ), and the variance- and bias-corrected f 2 ( f ^ 2 , vcbc ) are not suitable estimators due to higher-than-acceptable type I errors. The estimator f ^ 2 , exp , calculated based on the mathematical expectation of f ^ 2 , and f ^ 2 , vcexp , the variance-corrected f ^ 2 , exp , showed acceptable type I errors when combined with any of the ten percentile intervals. However, they have the drawback of low power, which might be addressed by increasing the sample size. To properly control the type I error, samples with at least 12 units should be used. Conclusion: The best combinations of estimator and type of confidence interval are f ^ 2 , exp and f ^ 2 , vcexp combined with any of the ten types of percentile intervals. When the sample f 2 value is close to 50, the use of the confidence interval of f 2 is recommended even when the variability of the dissolution profiles is low and the prerequisites defined in the regulatory guidelines for using the conventional f 2 method are fulfilled in order to control the type I error rate.
year | journal | country | edition | language |
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2021-11-01 | Computer Methods and Programs in Biomedicine |