PPQplan - Process Performance Qualification (PPQ) Plans in Chemistry, Manufacturing and Controls (CMC) Statistical Analysis
Assessment for statistically-based PPQ sampling plan, including calculating the passing probability, optimizing the baseline and high performance cutoff points, visualizing the PPQ plan and power dynamically. The analytical idea is based on the simulation methods from the textbook Burdick, R. K., LeBlond, D. J., Pfahler, L. B., Quiroz, J., Sidor, L., Vukovinsky, K., & Zhang, L. (2017). Statistical Methods for CMC Applications. In Statistical Applications for Chemistry, Manufacturing and Controls (CMC) in the Pharmaceutical Industry (pp. 227-250). Springer, Cham.
Last updated 3 years ago
biostatisticspharmaceuticalssampling-methods
4.11 score 1 stars 13 scripts 152 downloadsFixSeqMTP - Fixed Sequence Multiple Testing Procedures
Several generalized / directional Fixed Sequence Multiple Testing Procedures (FSMTPs) are developed for testing a sequence of pre-ordered hypotheses while controlling the FWER, FDR and Directional Error (mdFWER). All three FWER controlling generalized FSMTPs are designed under arbitrary dependence, which allow any number of acceptances. Two FDR controlling generalized FSMTPs are respectively designed under arbitrary dependence and independence, which allow more but a given number of acceptances. Two mdFWER controlling directional FSMTPs are respectively designed under arbitrary dependence and independence, which can also make directional decisions based on the signs of the test statistics. The main functions for each proposed generalized / directional FSMTPs are designed to calculate adjusted p-values and critical values, respectively. For users' convenience, the functions also provide the output option for printing decision rules.
Last updated 5 years ago
multiple-testingpre-ordersequential-testing
3.22 score 3 stars 11 scripts 167 downloadsMHTdiscrete - Multiple Hypotheses Testing for Discrete Data
A comprehensive tool for almost all existing multiple testing methods for discrete data. The package also provides some novel multiple testing procedures controlling FWER/FDR for discrete data. Given discrete p-values and their domains, the [method].p.adjust function returns adjusted p-values, which can be used to compare with the nominal significant level alpha and make decisions. For users' convenience, the functions also provide the output option for printing decision rules.
Last updated 5 years ago
adjustment-computationsbenjamini-hochbergbonferronidiscrete-distributionsmultiple-testing-correction
3.20 score 1 stars 32 scripts 280 downloadsADCT - Adaptive Design in Clinical Trials
Existing adaptive design methods in clinical trials. The package includes power, stopping boundaries (sample size) calculation functions for two-group group sequential designs, adaptive design with coprimary endpoints, biomarker-informed adaptive design, etc.
Last updated 3 years ago
3.00 score 5 scripts 253 downloadsMHTmult - Multiple Hypotheses Testing for Multiple Families/Groups Structure
A Comprehensive tool for almost all existing multiple testing methods for multiple families. The package summarizes the existing methods for multiple families multiple testing procedures (MTPs) such as double FDR, group Benjamini-Hochberg (GBH) procedure and average FDR controlling procedure. The package also provides some novel multiple testing procedures using selective inference idea.
Last updated 3 years ago
hierarchical-datamultiple-testingmultiplicity
2.70 score 9 scripts 126 downloadsph2mult - Phase II Clinical Trial Design for Multinomial Endpoints
Provide multinomial design methods under intersection-union test (IUT) and union-intersection test (UIT) scheme for Phase II trial. The design types include : Minimax (minimize the maximum sample size), Optimal (minimize the expected sample size), Admissible (minimize the Bayesian risk) and Maxpower (maximize the exact power level).
Last updated 8 years ago
1.48 score 1 packages 6 scripts 122 downloadsph2bye - Phase II Clinical Trial Design Using Bayesian Methods
Calculate the Bayesian posterior/predictive probability and determine the sample size and stopping boundaries for single-arm Phase II design.
Last updated 8 years ago
1.30 score 2 stars 10 scripts 167 downloads