arXiv subjects

Kunhai Qing

Publications and source records attributed to Kunhai Qing.

3 recordsLinked to original sources

arXiv2026

Consistency Assessment of Regional Treatment Effect for Multi-Regional Clinical Trials in the Presence of Covariate Shift

Multi-Regional Clinical Trials (MRCTs) play a central role in the development of new therapies by enabling the simultaneous evaluation of drug efficacy and safety across diverse global populations. Assessing the consistency of treatment effects across regions is a fundamental aspect of MRCTs. Existing methods typically focus on region-specific marginal treatment effects. However, when treatment effect heterogeneity arises due to effect-modifying baseline covariates, distributional differences in these covariates can lead to erroneous conclusions. In this paper, we explicitly account for this phenomenon in the consistency assessment by considering the conditional average treatment effect. We propose a two-step assessment strategy that complements existing methods and mitigates the impact of treatment effect heterogeneity. Results from numerical studies demonstrate the effectiveness of the proposed approach.

stat.AP↗

arXiv2025

BKP: An R Package for Beta Kernel Process Modeling

Estimating input-dependent probability surfaces from binary, binomial, categorical, or multinomial response data is a common task in statistics and machine learning. Latent Gaussian process classifiers provide flexible nonparametric models for such problems, but posterior inference with discrete responses typically requires approximation or simulation. We discuss an implementation of probability-scale beta and Dirichlet kernel models in the \pkg{BKP} package for \proglang{R}. The package implements the Beta Kernel Process (BKP), which uses kernel-weighted pseudo-count aggregation and beta-binomial conjugacy to obtain closed-form conjugate posterior summaries and posterior predictive distributions for binomial probabilities. It also implements the Dirichlet Kernel Process (DKP) for multi-class responses, together with TwinBKP and TwinDKP, scalable twinning-based global-local approximations for larger datasets. The resulting workflow supports transparent kernel-weighted evidence borrowing, several kernel families, fixed and data-adaptive priors, effective-sample-size calibration, loss-based hyperparameter tuning, and standard S3 methods for fitting, prediction, simulation, visualization, and extraction of posterior summaries. Reproducible examples demonstrate probability-surface estimation, binary and multi-class classification, computational comparison, and real-data applications to \emph{Loa loa} infection prevalence mapping and Mourning Warbler distribution modeling.

stat.CO↗

arXiv2025

Regional consistency evaluation and sample size calculation under two MRCTs

Multi-regional clinical trial (MRCT) has been common practice for drug development and global registration. The FDA guidance `Demonstrating Substantial Evidence of Effectiveness for Human Drug and Biological Products Guidance for Industry' (FDA, 2019) requires that substantial evidence of effectiveness of a drug/biologic product to be demonstrated for market approval. In the situations where two pivotal MRCTs are needed to establish effectiveness of a specific indication for a drug or biological product, a systematic approach of consistency evaluation for regional effect is crucial. In this paper, we first present some existing regional consistency evaluations in a unified way that facilitates regional sample size calculation under the simple fixed effects model. Second, we extend the two commonly used consistency assessment criteria of MHLW (2007) in the context of two MRCTs and provide their evaluation and regional sample size calculation. Numerical studies demonstrate the proposed regional sample size attains the desired probability of showing regional consistency. A hypothetical example is presented to illustrate the application. We provide an R package for implementation.

stat.AP↗