NHS and Healthcare-Related Data for Education and Training

Free United Kingdom National Health Service (NHS) and other healthcare, or population health-related data for education and training purposes. This package contains synthetic data based on real healthcare datasets, or cuts of open-licenced official data. This package exists to support skills development in the NHS-R community: < https://nhsrcommunity.com/>.

Bias-Corrected Sandwich Variance Estimators for Marginal Cox Analysis of Cluster Randomized Trials

The implementation of bias-corrected sandwich variance estimators for the analysis of cluster randomized trials with time-to-event outcomes using the marginal Cox model, proposed by Wang et al. (under review).

R Manuals Literally Translated in Korean

R version 2.1.0 and later support Korean translations of program messages. The continuous efforts have been made by < http://developer.r-project.org/TranslationTeams.html> The R Documentation files are licensed under the General Public License, version 2 or 3. This means that the pilot project to translate them into Korean has permission to reproduce them and translate them. This work is done with GNU 'gettext' utilities. The portable object template is updated a weekly basis or whenever changes are necessary. Comments and corrections via email to the maintainer is of course most welcome. In order to voluntarily participate in or offer your help with this translation, please contact the maintainer. To check the change and progress of Korean translation, please visit < http://www.openstatistics.net>.

Inhomogeneous K- And Pair Correlation Functions Using Global Estimators

Second-order summary statistics K- and pair-correlation functions describe interactions in point pattern data. This package provides computations to estimate those statistics on inhomogeneous point processes, using the methods of in T Shaw, J Møller, R Waagepetersen, 2020 .

Error Detection in Science

Test published summary statistics for consistency (Brown and Heathers, 2017, ; Allard, 2018, < https://aurelienallard.netlify.app/post/anaytic-grimmer-possibility-standard-deviations/>; Heathers and Brown, 2019, < https://osf.io/5vb3u/>). The package also provides infrastructure for implementing new error detection techniques.

Efficient Design and Analysis of Cluster Randomized Trials

Constrained randomization by Raab and Butcher (2001) is suitable for cluster randomized trials (CRTs) with a small number of clusters (e.g., 20 or fewer). The procedure of constrained randomization is based on the baseline values of some cluster-level covariates specified. The intervention effect on the individual outcome can then be analyzed through clustered permutation test introduced by Gail, et al. (1996) . Motivated from Li, et al. (2016) , the package performs constrained randomization on the baseline values of cluster-level covariates and clustered permutation test on the individual-level outcomes for cluster randomized trials.

Seasonal Mid-Summer Drought Characteristics

Characterization of a mid-summer drought (MSD) with precipitation based statistics. The MSD is a phenomenon of decreased rainfall during a typical rainy season. It is a feature of rainfall in much of Central America and is also found in other locations, typically those with a Mediterranean climate. Details on the metrics are in Maurer et al. (2022) .

Bias-Corrected GEE for Cluster Randomized Trials

Population-averaged models have been increasingly used in the design and analysis of cluster randomized trials (CRTs). To facilitate the applications of population-averaged models in CRTs, the package implements the generalized estimating equations (GEE) and matrix-adjusted estimating equations (MAEE) approaches to jointly estimate the marginal mean models correlation models both for general CRTs and stepped wedge CRTs. Despite the general GEE/MAEE approach, the package also implements a fast cluster-period GEE method by Li et al. (2022) specifically for stepped wedge CRTs with large and variable cluster-period sizes and gives a simple and efficient estimating equations approach based on the cluster-period means to estimate the intervention effects as well as correlation parameters. In addition, the package also provides functions for generating correlated binary data with specific mean vector and correlation matrix based on the multivariate probit method in Emrich and Piedmonte (1991) or the conditional linear family method in Qaqish (2003) .

Replicability Analysis for Multiple Studies of High Dimension

Estimation of Bayes and local Bayes false discovery rates for replicability analysis (Heller & Yekutieli, 2014 ; Heller at al., 2015 ).

Interactive Graphics Functions for the 'spatstat' Package

Extension to the 'spatstat' package, containing interactive graphics capabilities.