This package provides functions to get personal Google Scholar profile data from web API and show it in table or figure format.

Table, Listings, and Graphs (TLG) library for common outputs used in clinical trials.

This package provides functions for admin needs of employees of Thomas Jefferson University and Thomas Jefferson University Hospital, Philadelphia, PA.

This package provides tools for simulating and modeling traffic flow on road networks using spatial conditional autoregressive (CAR) models. The package represents road systems as graphs derived from OpenStreetMap data <https://www.openstreetmap.org/> and supports network-based spatial dependence, basic preprocessing, and visualization for spatial traffic analysis.

Transforms long data into a matrix form to allow for ease of input into modelling packages for regression, principal components, imputation or machine learning. It does this by pivoting on user defined columns, generating a key-value table for variable names to ensure one-to-one mappings are preserved. It is particularly useful when the indicator names in the columns are long descriptive strings, for example "Energy imports, net (% of energy use)". High level analysis wrapper functions for correlation and principal components analysis are provided.

The main goal of the R package treeDbalance is to provide functions for the computation of several measurements of 3D node imbalance and their respective 3D tree imbalance indices, as well as to introduce the new phylo3D format for rooted 3D tree objects. Moreover, it encompasses an example dataset of 3D models of 63 beans in phylo3D format. Please note that this R package was developed alongside the project described in the manuscript Measuring 3D tree imbalance of plant models using graph-theoretical approaches by M. Fischer, S. Kersting, and L. Kühn (2023) <arXiv:2307.14537>, which provides precise mathematical definitions of the measurements. Furthermore, the package contains several helpful functions, for example, some auxiliary functions for computing the ancestors, descendants, and depths of the nodes, which ensures that the computations can be done in linear time. Most functions of treeDbalance require as input a rooted tree in the phylo3D format, an extended phylo format (as introduced in the R package ape 1.9 in November 2006). Such a phylo3D object must have at least two new attributes next to those required by the phylo format: node.coord', the coordinates of the nodes, as well as edge.weight', the literal weight or volume of the edges. Optional attributes are edge.diam', the diameter of the edges, and edge.length', the length of the edges. For visualization purposes one can also specify edge.type', which ranges from normal cylinder to bud to leaf, as well as edge.color to change the color of the edge depiction. This project was supported by the joint research project DIG-IT! funded by the European Social Fund (ESF), reference: ESF/14-BM-A55-0017/19, and the Ministry of Education, Science and Culture of Mecklenburg-Western Pomerania, Germany, as well as by the the project ArtIGROW, which is a part of the WIR!-Alliance ArtIFARM â Artificial Intelligence in Farming funded by the German Federal Ministry of Education and Research (FKZ: 03WIR4805).

Simplify reporting many tables by creating tibbles of tables. With tabtibble', a tibble of tables is created with captions and automatic printing using knit_print()'.

Obtain population density and body size structure, using video material or image sequences as input. Functions assist in the creation of image sequences from videos, background detection and subtraction, particle identification and tracking. An artificial neural network can be trained for noise filtering. The goal is to supply accurate estimates of population size, structure and/or individual behavior, for use in evolutionary and ecological studies.

This package provides a tool to obtain tumor growth rates from clinical trial patient data. Output includes individual and summary data for tumor growth rate estimates as well as optional plots of the observed and predicted tumor quantity over time.

This package implements a semiparametric estimator for the odds ratio model with censored, time-lagged, ordered categorical outcome in a randomized clinical trial that incorporates baseline and time-dependent information. Tsiatis AA, Davidian M, Holloway ST (2023) <doi:10.1111/biom.13603>.

Performing the hypothesis tests for the two sample problem based on order statistics and power comparisons. Calculate the test statistic, density, distribution function, quantile function, random number generation and others.

This package provides a shiny based interactive exploration framework for analyzing clinical trials data. teal currently provides a dynamic filtering facility and different data viewers. teal shiny applications are built using standard shiny modules.

An interface to the mclust package to easily carry out latent profile analysis ("LPA"). Provides functionality to estimate commonly-specified models. Follows a tidy approach, in that output is in the form of a data frame that can subsequently be computed on. Also has functions to interface to the commercial MPlus software via the MplusAutomation package.

This package provides multiple water chemistry-based models and published empirical models in one standard format. As many models have been included as possible, however, users should be aware that models have varying degrees of accuracy and applicability. To learn more, read the references provided below for the models implemented. Functions can be chained together to model a complete treatment process and are designed to work in a tidyverse workflow. Models are primarily based on these sources: Benjamin, M. M. (2002, ISBN:147862308X), Crittenden, J. C., Trussell, R., Hand, D., Howe, J. K., & Tchobanoglous, G., Borchardt, J. H. (2012, ISBN:9781118131473), USEPA. (2001) <https://www.epa.gov/sites/default/files/2017-03/documents/wtp_model_v._2.0_manual_508.pdf>.

This package provides a collection of functions to plot acid/base titration curves (pH vs. volume of titrant), complexation titration curves (pMetal vs. volume of EDTA), redox titration curves (potential vs.volume of titrant), and precipitation titration curves (either pAnalyte or pTitrant vs. volume of titrant). Options include the titration of mixtures, the ability to overlay two or more titration curves, and the ability to show equivalence points.

Tautulli (<http://tautulli.com>) is a monitoring application for Plex Media Servers (<https://www.plex.tv>) which collects a lot of data about media items and server usage such as play counts. This package interacts with the Tautulli API of any specified server to get said data into R. The Tautulli API documentation is available at <https://github.com/Tautulli/Tautulli/blob/master/API.md>.

This package provides a simple type annotation for R that is usable in scripts, in the R console and in packages. It is intended as a convention to allow other packages to use the type information to provide error checking, automatic documentation or optimizations.

Simulate phase II and/or phase III clinical trials. It supports various types of endpoints and adaptive strategies. Tools for carrying out graphical testing procedure and combination test under group sequential design are also provided.

Built on top of the tibble package, tibbletime is an extension that allows for the creation of time aware tibbles. Some immediate advantages of this include: the ability to perform time-based subsetting on tibbles, quickly summarising and aggregating results by time periods, and creating columns that can be used as dplyr time-based groups.

An R wrapper for the Spotify Web API <https://developer.spotify.com/web-api/>.

This package provides an integrated user interface and workflow for the analysis of running, cycling and swimming data from GPS-enabled tracking devices through the trackeR <https://CRAN.R-project.org/package=trackeR> R package.

The Tanaka method enhances the representation of topography on a map using shaded contour lines. In this simplified implementation of the method, north-west white contours represent illuminated topography and south-east black contours represent shaded topography. See Tanaka (1950) <doi:10.2307/211219>.

This package provides methods for computing joint tests, controlling the Familywise Error Rate (FWER) and getting lower bounds on the number of false hypotheses in a set. The methods implemented here are described in Mogensen and Markussen (2021) <doi:10.48550/arXiv.2108.04731>.

Comprehensive functions to calculate sample size and power for clinical trials with two co-primary endpoints. The package supports five endpoint combinations: two continuous endpoints (Sozu et al. 2011 <doi:10.1080/10543406.2011.551329>), two binary endpoints using asymptotic methods (Sozu et al. 2010 <doi:10.1002/sim.3972>) and exact methods (Homma and Yoshida 2025 <doi:10.1177/09622802251368697>), mixed continuous and binary endpoints (Sozu et al. 2012 <doi:10.1002/bimj.201100221>), and mixed count and continuous endpoints (Homma and Yoshida 2024 <doi:10.1002/pst.2337>). All methods appropriately account for correlation between endpoints and provide both sample size and power calculation capabilities.