Bootstrap confidence intervals for dissolution similarity factor f2

Abstract

Parametric and non-parametric bootstrap methods are used to investigate the statistical properties of the dissolution similarity factor . The main objective of this study is to compare the results obtained by these two methods. We estimate characteristics of the sampling distribution of statistic under these methods with various bootstrap sample sizes using Monte Carlo simulation. A number of bootstrap confidence interval (CI) construction techniques are used to determine a 90 % CI for the true value of under both parametric and non-parametric schemes. The bootstrap sampling distributions of under both schemes are found to be approximately symmetrical with a non-zero excess of kurtosis. Non-parametric bootstrap confidence intervals for perform better than those obtained from parametric methods. The Bias corrected (BC) and accelerated bootstrap percentile (BCa) confidence interval method produce more precise two-sided confidence intervals for compared to other methods