Parse messy geographic coordinates from various character formats to decimal degree numeric values. Parse coordinates into their parts (degree, minutes, seconds); calculate hemisphere from coordinates; pull out individually degrees, minutes, or seconds; add and subtract degrees, minutes, and seconds. C++ code herein originally inspired from code written by Jeffrey D. Bogan, but then completely re-written.

Applies phylogenetic comparative methods (PCM) and phylogenetic trait imputation using structural equation models (SEM), extending methods from Thorson et al. (2023) <doi:10.1111/2041-210X.14076>. This implementation includes a minimal set of features, to allow users to easily read all of the documentation and source code. PCM using SEM includes phylogenetic linear models and structural equation models as nested submodels, but also allows imputation of missing values. Features and comparison with other packages are described in Thorson and van der Bijl (2023) <doi:10.1111/jeb.14234>.

This package provides various functions for retrieving and interpreting information from Pubmed via the API, <https://www.ncbi.nlm.nih.gov/home/develop/api/>.

Shiny app to interactively visualize hierarchical clustering with prototypes. For details on hierarchical clustering with prototypes, see Bien and Tibshirani (2011) <doi:10.1198/jasa.2011.tm10183>. This package currently launches the application.

This package provides tools for downloading, reading and analyzing the National Survey of Health - PNS, a household survey from Brazilian Institute of Geography and Statistics - IBGE. The data must be downloaded from the official website <https://www.ibge.gov.br/>. Further analysis must be made using package survey'.

Infer the genetic composition of individuals in terms of haplotype dosages for a haploblock, based on bi-allelic marker dosages, for any ploidy level. Reference: Voorrips and Tumino: PolyHaplotyper: haplotyping in polyploids based on bi-allelic marker dosage data. Submitted to BMC Bioinformatics (2021).

Psychometric mixture models based on flexmix infrastructure. At the moment Rasch mixture models with different parameterizations of the score distribution (saturated vs. mean/variance specification), Bradley-Terry mixture models, and MPT mixture models are implemented. These mixture models can be estimated with or without concomitant variables. See Frick et al. (2012) <doi:10.18637/jss.v048.i07> and Frick et al. (2015) <doi:10.1177/0013164414536183> for details on the Rasch mixture models.

This package provides data sets and functions for exploration of Pakistan Population Census 2017 (<http://www.pbscensus.gov.pk/>).

Helper functions for package creation, building and maintenance. Designed to work with a build system such as GNU make or package fakemake to help you to conditionally work through the stages of package development (such as spell checking, linting, testing, before building and checking a package).

This package provides a set of Analysis Data Model (ADaM) datasets constructed using the Study Data Tabulation Model (SDTM) datasets contained in the pharmaversesdtm package and the template scripts from the admiral family of packages. ADaM dataset specifications are described in the CDISC ADaM implementation guide, accessible by creating a free account on <https://www.cdisc.org/>.

Provide summary table of daily physical activity and per-person/grouped heat map for accelerometer data from SenseWear Armband. See <https://templehealthcare.wordpress.com/the-sensewear-armband/> for more information about SenseWear Armband.

Utility functions produced specifically for (but not limited to) working with ProjectTemplate data pipelines. This package helps to quickly create and manage sequentially numbered scripts, quickly set up logging with log4r and functions to help debug and monitor procedures.

Analysis of terms in linear, generalized and mixed linear models, on the basis of multiple comparisons of factor contrasts. Specially suited for the analysis of interaction terms.

This package contains tools for supervised analyses of incomplete, overlapping multiomics datasets. Applies partial least squares in multiple steps to find models that predict survival outcomes. See Yamaguchi et al. (2023) <doi:10.1101/2023.03.10.532096>.

This package contains functions to run propensity-biased allocation to balance covariate distributions in sequential trials and propensity-constrained randomization to balance covariate distributions in trials with known baseline covariates at time of randomization. Currently only supports trials comparing two groups.

This package provides a set of Study Data Tabulation Model (SDTM) datasets from the Clinical Data Interchange Standards Consortium (CDISC) pilot project used for testing and developing Analysis Data Model (ADaM) datasets inside the pharmaverse family of packages. SDTM dataset specifications are described in the CDISC SDTM implementation guide, accessible by creating a free account on <https://www.cdisc.org/>.

Kappa, ICC, reliability coefficient, parallel analysis, multi-traits multi-methods, spherical representation of a correlation matrix.

Adds different kinds of brackets to a plot, including braces, chevrons, parentheses or square brackets.

Creation of linkage maps in polyploid species from marker dosage scores of an F1 cross from two heterozygous parents. Currently works for outcrossing diploid, autotriploid, autotetraploid and autohexaploid species, as well as segmental allotetraploids. Methods are described in a manuscript of Bourke et al. (2018) <doi:10.1093/bioinformatics/bty371>. Since version 1.1.0, both discrete and probabilistic genotypes are acceptable input; for more details on the latter see Liao et al. (2021) <doi:10.1007/s00122-021-03834-x>.

An implementation of a formal grammar and parser for R Markdown documents using the Boost Spirit X3 library. It also includes a collection of high level functions for working with the resulting abstract syntax tree.

References and cites R and R packages on the fly in R Markdown and Quarto'. pakret provides a minimalist API that generates preformatted citations for R and R packages, and adds their references to a .bib file directly from within your document.

In the era of big data, data redundancy and distributed characteristics present novel challenges to data analysis. This package introduces a method for estimating optimal subsets of redundant distributed data, based on PPCDT (Conjunction of Power and P-value in Distributed Settings). Leveraging PPC technology, this approach can efficiently extract valuable information from redundant distributed data and determine the optimal subset. Experimental results demonstrate that this method not only enhances data quality and utilization efficiency but also assesses its performance effectively. The philosophy of the package is described in Guo G. (2020) <doi:10.1007/s00180-020-00974-4>.

Engineered features and "helper" functions ancillary to the public.ctn0094data package, extending this package for ease of use (see <https://CRAN.R-project.org/package=public.ctn0094data>). This public.ctn0094data package contains harmonized datasets from some of the National Institute of Drug Abuse's Clinical Trials Network (NIDA's CTN) projects. Specifically, the CTN-0094 project is to harmonize and de-identify clinical trials data from the CTN-0027, CTN-0030, and CTN-51 studies for opioid use disorder. This current version is built from public.ctn0094data v. 1.0.6.

This package provides classes to pre-process microarray gene expression data as part of the OOMPA collection of packages described at <http://oompa.r-forge.r-project.org/>.