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Phase-3 clinical trials provide the highest level of evidence on drug safety and effectiveness needed for market approval by implementing large randomized controlled trials (RCTs). However, 30-40% of these trials fail mainly because such…

Applications · Statistics 2024-01-09 Sayeri Lala , Niraj K. Jha

The TrendLSW R package has been developed to provide users with a suite of wavelet-based techniques to analyse the statistical properties of nonstationary time series. The key components of the package are (a) two approaches for the…

Methodology · Statistics 2024-11-06 Euan T. McGonigle , Rebecca Killick , Matthew A. Nunes

The concept of concurrent mental health and substance use (MHSU) and its detection in patients has garnered growing interest among psychiatrists and healthcare policymakers over the past four decades. Researchers have proposed various…

Methodology · Statistics 2025-04-25 Mohsen Soltanifar , Chel Hee Lee

Item response theory (IRT) models are a class of statistical models used to describe the response behaviors of individuals to a set of items having a certain number of options. They are adopted by researchers in social science, particularly…

Computation · Statistics 2014-04-16 Angelo Mazza , Antonio Punzo , Brian McGuire

Objective: To provide guidance for the use of the main functions available in R for performing post hoc Bayesian analysis of a randomized clinical trial with a survival endpoint using proportional hazard models. Study Design and Setting:…

Computation · Statistics 2019-09-10 Lucie Biard , Anne Bergeron , Sylvie Chevret

Simulation offers a simple and flexible way to estimate the power of a clinical trial when analytic formulae are not available. The computational burden of using simulation has, however, restricted its application to only the simplest of…

Statistical techniques are used in all branches of science to determine the feasibility of quantitative hypotheses. One of the most basic applications of statistical techniques in comparative analysis is the test of equality of two…

Methodology · Statistics 2018-05-01 Ayanendranath Basu , Abhijit Mandal , Nirian Martin , Leandro Pardo

Testing differences between a treatment and control group is common practice in biomedical research like randomized controlled trials (RCT). The standard two-sample t-test relies on null hypothesis significance testing (NHST) via p-values,…

Methodology · Statistics 2020-05-18 Riko Kelter

Background: Current nomogram can only be created for regression algorithm. Providing nomogram for any machine learning (ML) algorithms may accelerate model deployment in clinical settings or improve model availability. We developed an R…

Machine Learning · Computer Science 2025-01-13 Herdiantri Sufriyana , Emily Chia-Yu Su

Multi-regional clinical trials (MRCTs) have become common practice for drug development and global registration. Once overall significance is established, demonstrating regional consistency is critical for local health authorities. Methods…

Methodology · Statistics 2025-08-14 Xinru Ren , Jin Xu

Utilizing Bayesian methods in clinical trials has become increasingly popular, as they can incorporate historical data and expert opinions into the design and allow for smaller sample sizes to reduce costs while providing reliable and…

We extend a general approach to evaluating identification risk of synthesized variables in partially synthetic data. For multiple continuous synthesized variables, we introduce the use of a radius $r$ in the construction of identification…

Methodology · Statistics 2021-04-07 Ryan Hornby , Jingchen Hu

In \textit{computer-based testing} it has become standard to collect response accuracy (RA) and response times (RTs) for each test item. IRT models are used to measure a latent variable (e.g., ability, intelligence) using the RA…

Methodology · Statistics 2021-06-21 Jean-Paul Fox , Konrad Klotzke , Ahmet Salih Simsek

Estimating sample size and statistical power is an essential part of a good study design. This R package allows users to conduct power analysis based on Monte Carlo simulations in settings in which consideration of the correlations between…

Methodology · Statistics 2024-04-16 Phuc H. Nguyen , Stephanie M. Engel , Amy H. Herring

In many settings, robust data analysis involves computational methods for uncertainty quantification and statistical inference. To design frequentist studies that leverage robust analysis methods, suitable sample sizes to achieve desired…

Methodology · Statistics 2025-12-19 Luke Hagar , Andrew J. Martin

A plethora of disparate statistical methods have been proposed for subgroup identification to help tailor treatment decisions for patients. However a majority of them do not have corresponding R packages and the few that do pertain to…

Computation · Statistics 2018-11-14 Jared D. Huling , Menggang Yu

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'…

Applications · Statistics 2025-07-22 Kunhai Qing , Xinru Ren , Shuping Jiang , Ping Yang , Menggang Yu , Jin Xu

In this article, we introduce the R package portes with extensive illustrative applications. The asymptotic distributions and the Monte Carlo procedures of the most popular univariate and multivariate portmanteau test statistics, including…

Applications · Statistics 2020-05-05 Esam Mahdi

Determining whether perceptual properties are processed independently is an important goal in perceptual science, and tools to test independence should be widely available to experimental researchers. The best analytical tools to test for…

Neurons and Cognition · Quantitative Biology 2016-10-12 Fabian A. Soto , Emily Zheng , Johnny Fonseca , F. Greg Ashby

The R package robusTest offers corrected versions of several common tests in bivariate statistics. We point out the limitations of these tests in their classical versions, some of which are well known such as robustness or calibration…