Estimates the pooled (unadjusted) Receiver Operating Characteristic (ROC) curve, the covariate-adjusted ROC (AROC) curve, and the covariate-specific/conditional ROC (cROC) curve by different methods, both Bayesian and frequentist. Also, it provides functions to obtain ROC-based optimal cutpoints utilizing several criteria. Based on Erkanli, A. et al. (2006) <doi:10.1002/sim.2496>; Faraggi, D. (2003) <doi:10.1111/1467-9884.00350>; Gu, J. et al. (2008) <doi:10.1002/sim.3366>; Inacio de Carvalho, V. et al. (2013) <doi:10.1214/13-BA825>; Inacio de Carvalho, V., and Rodriguez-Alvarez, M.X. (2022) <doi:10.1214/21-STS839>; Janes, H., and Pepe, M.S. (2009) <doi:10.1093/biomet/asp002>; Pepe, M.S. (1998) <http://www.jstor.org/stable/2534001?seq=1>; Rodriguez-Alvarez, M.X. et al. (2011a) <doi:10.1016/j.csda.2010.07.018>; Rodriguez-Alvarez, M.X. et al. (2011a) <doi:10.1007/s11222-010-9184-1>. Please see Rodriguez-Alvarez, M.X. and Inacio, V. (2021) <doi:10.32614/RJ-2021-066> for more details.

DBI/RJDBC interface to h2 database. h2 version 2.3.232 is included.

Cross-Linguistic Data Format (CLDF) is a framework for storing cross-linguistic data, ensuring compatibility and ease of data exchange between different linguistic datasets see Forkel et al. (2018) <doi:10.1038/sdata.2018.205>. The rcldf package is designed to facilitate the manipulation and analysis of these datasets by simplifying the loading, querying, and visualisation of CLDF datasets making it easier to conduct comparative linguistic analyses, manage language data, and apply statistical methods directly within R.

Rasch model and extensions for survey data, using Conditional Maximum likelihood (CML). Carlo Cafiero, Sara Viviani, Mark Nord (2018) <doi:10.1016/j.measurement.2017.10.065>.

Supports automated Markov chain Monte Carlo for arbitrarily structured correlation matrices. The user supplies data, a correlation matrix in symbolic form, the current state of the chain, a function that computes the log likelihood, and a list of prior distributions. The package's flagship function then carries out a parameter-at-a-time update of all correlation parameters, and returns the new state. The method is presented in Hughes (2023), in preparation.

R Commander plug-in for repeated-measures and mixed-design ('split-plot') ANOVA. It adds a new menu entry for repeated measures that allows to deal with up to three within-subject factors and optionally with one or several between-subject factors. It also provides supplementary options to oneWayAnova() and multiWayAnova() functions, such as choice of ANOVA type, display of effect sizes and post hoc analysis for multiWayAnova().

This package provides tools for randomization-based inference. Current focus is on the d^2 omnibus test of differences of means following Hansen and Bowers (2008) <doi:10.1214/08-STS254> . This test is useful for assessing balance in matched observational studies or for analysis of outcomes in block-randomized experiments.

Interface for loading data from Google Ads API', see <https://developers.google.com/google-ads/api/docs/start>. Package provide function for authorization and loading reports.

Aggregates multiple Receiver Operating Characteristic (ROC) curves obtained from different sources into one global ROC. Additionally, itâ s also possible to calculate the aggregated precision-recall (PR) curve.

Implementation of the RPC-JSON API for Bitcoin and utility functions for address creation and content analysis of the blockchain.

This package provides a small language extension for succinct conditional assignment using `?` and `:`, emulating the conditional ternary operator syntax using in C, Java, JavaScript and other languages.

The provided benchmark suite enables the automated evaluation and comparison of any existing and novel indirect method for reference interval ('RI') estimation in a systematic way. Indirect methods take routine measurements of diagnostic tests, containing pathological and non-pathological samples as input and use sophisticated statistical methods to derive a model describing the distribution of the non-pathological samples, which can then be used to derive reference intervals. The benchmark suite contains 5,760 simulated test sets with varying difficulty. To include any indirect method, a custom wrapper function needs to be provided. The package offers functions for generating the test sets, executing the indirect method and evaluating the results. See ?RIbench or vignette("RIbench_package") for a more comprehensive description of the features. A detailed description and application is described in Ammer T., Schuetzenmeister A., Prokosch H.-U., Zierk J., Rank C.M., Rauh M. "RIbench: A Proposed Benchmark for the Standardized Evaluation of Indirect Methods for Reference Interval Estimation". Clinical Chemistry (2022) <doi:10.1093/clinchem/hvac142>.

Implementation of Taylor Regression Estimator (TRE), Tulip Extreme Finding Estimator (TEFE), Bell Extreme Finding Estimator (BEFE), Integration Extreme Finding Estimator (IEFE) and Integration Root Finding Estimator (IRFE) for roots, extrema and inflections of a curve . Christopoulos, DT (2019) <doi:10.13140/RG.2.2.17158.32324> . Christopoulos, DT (2016) <doi:10.2139/ssrn.3043076> . Christopoulos, DT (2016) <https://demovtu.veltech.edu.in/wp-content/uploads/2016/04/Paper-04-2016.pdf> . Christopoulos, DT (2014) <doi:10.48550/arXiv.1206.5478> .

The SPRITE algorithm creates possible distributions of discrete responses based on reported sample parameters, such as mean, standard deviation and range (Heathers et al., 2018, <doi:10.7287/peerj.preprints.26968v1>). This package implements it, drawing heavily on the code for Nick Brown's rSPRITE Shiny app <https://shiny.ieis.tue.nl/sprite/>. In addition, it supports the modeling of distributions based on multi-item (Likert-type) scales and the use of restrictions on the frequency of particular responses.

The RCC_PCA criterion is a tool to determine the optimal number of components to retain in PCA;See Alshammri (2021).

The aim of this package is to manipulate relational data models in R. It provides functions to create, modify and export data models in json format. It also allows importing models created with MySQL Workbench (<https://www.mysql.com/products/workbench/>). These functions are accessible through a graphical user interface made with shiny'. Constraints such as types, keys, uniqueness and mandatory fields are automatically checked and corrected when editing a model. Finally, real data can be confronted to a model to check their compatibility.

An extension for roxygen2 to embed Shinylive applications in the package documentation.

Numerous functions for cohort-based analyses, either for prediction or causal inference. For causal inference, it includes Inverse Probability Weighting and G-computation for marginal estimation of an exposure effect when confounders are expected. We deal with binary outcomes, times-to-events, competing events, and multi-state data. For multistate data, semi-Markov model with interval censoring may be considered, and we propose the possibility to consider the excess of mortality related to the disease compared to reference lifetime tables. For predictive studies, we propose a set of functions to estimate time-dependent receiver operating characteristic (ROC) curves with the possible consideration of right-censoring times-to-events or the presence of confounders. Finally, several functions are available to assess time-dependent ROC curves or survival curves from aggregated data.

This package provides an interface to the Spotify API <https://developer.spotify.com/documentation/web-api/>.

Analysis of combined total and allele specific reads from the reciprocal cross study with RNA-seq data.

Utilities for accessing RePEc (Research Papers in Economics) through a RESTful API. You can request a code and get detailed information at the following page: <https://ideas.repec.org/api.html>.

Statistical estimation of revealed preference models from data collected on bipartite matchings. The models are for matchings within a bipartite population where individuals have utility for people based on known and unknown characteristics. People can form a partnership or remain unpartnered. The model represents both the availability of potential partners of different types and preferences of individuals for such people. The software estimates preference parameters based on sample survey data on partnerships and population composition. The simulation of matchings and goodness-of-fit are considered. See Goyal, Handcock, Jackson, Rendall and Yeung (2022) <doi:10.1093/jrsssa/qnad031>.

Real Twig is a method to correct branch overestimation in quantitative structure models. Overestimated cylinders are correctly tapered using measured twig diameters of corresponding tree species. Supported quantitative structure modeling software includes TreeQSM', SimpleForest', Treegraph', and aRchi'. Also included is a novel database of twig diameters and tools for fractal analysis of point clouds.

This package provides a user-friendly interface for managing PostgreSQL database connection settings. The package supplies helper functions to create, edit and load connection and option configuration files stored in a user-specific directory using the odbc and RPostgres back ends. These helpers make it easy to construct a reproducible connection string from a configuration file, either by reading user-defined YAML files or by parsing an environment variable.