Showing 14 of total 14 results (show query)
raybaser
PROscorer:Functions to Score Commonly-Used Patient-Reported Outcome (PRO) Measures and Other Psychometric Instruments
An extensible repository of accurate, up-to-date functions to score commonly used patient-reported outcome (PRO), quality of life (QOL), and other psychometric and psychological measures. 'PROscorer', together with the 'PROscorerTools' package, is a system to facilitate the incorporation of PRO measures into research studies and clinical settings in a scientifically rigorous and reproducible manner. These packages and their vignettes are intended to help establish and promote best practices for scoring PRO and PRO-like measures in research. The 'PROscorer' Instrument Descriptions vignette contains descriptions of each instrument scored by 'PROscorer', complete with references. These instrument descriptions are suitable for inclusion in formal study protocol documents, grant proposals, and manuscript Method sections. Each 'PROscorer' function is composed of helper functions from the 'PROscorerTools' package, and users are encouraged to contribute new functions to 'PROscorer'. More scoring functions are currently in development and will be added in future updates.
Maintained by Ray Baser. Last updated 5 months ago.
clinical-trialsprospsychometricsqolquality-of-lifequality-of-life-questionnairer-pkgscoring
11.0 match 4 stars 4.75 score 14 scripts
mskcc-epi-bio
PROscorerTools:Tools to Score Patient-Reported Outcome (PRO) and Other Psychometric Measures
Provides a reliable and flexible toolbox to score patient-reported outcome (PRO), Quality of Life (QOL), and other psychometric measures. The guiding philosophy is that scoring errors can be eliminated by using a limited number of well-tested, well-behaved functions to score PRO-like measures. The workhorse of the package is the 'scoreScale' function, which can be used to score most single-scale measures. It can reverse code items that need to be reversed before scoring and pro-rate scores for missing item data. Currently, three different types of scores can be output: summed item scores, mean item scores, and scores scaled to range from 0 to 100. The 'PROscorerTools' functions can be used to write new functions that score more complex measures. In fact, 'PROscorerTools' functions are the building blocks of the scoring functions in the 'PROscorer' package (which is a repository of functions that score specific commonly-used instruments). Users are encouraged to use 'PROscorerTools' to write scoring functions for their favorite PRO-like instruments, and to submit these functions for inclusion in 'PROscorer' (a tutorial vignette will be added soon). The long-term vision for the 'PROscorerTools' and 'PROscorer' packages is to provide an easy-to-use system to facilitate the incorporation of PRO measures into research studies in a scientifically rigorous and reproducible manner. These packages and their vignettes are intended to help establish and promote "best practices" for scoring and describing PRO-like measures in research.
Maintained by Ray Baser. Last updated 1 years ago.
clinical-trialsprospsychometricsqolquality-of-lifequestionnairesurvey
11.0 match 2 stars 4.73 score 18 scripts 1 dependents
bioconductor
BiocManager:Access the Bioconductor Project Package Repository
A convenient tool to install and update Bioconductor packages.
Maintained by Marcel Ramos. Last updated 1 months ago.
1.5 match 74 stars 16.47 score 2.9k scripts 414 dependentsbioc
pathwayPCA:Integrative Pathway Analysis with Modern PCA Methodology and Gene Selection
pathwayPCA is an integrative analysis tool that implements the principal component analysis (PCA) based pathway analysis approaches described in Chen et al. (2008), Chen et al. (2010), and Chen (2011). pathwayPCA allows users to: (1) Test pathway association with binary, continuous, or survival phenotypes. (2) Extract relevant genes in the pathways using the SuperPCA and AES-PCA approaches. (3) Compute principal components (PCs) based on the selected genes. These estimated latent variables represent pathway activities for individual subjects, which can then be used to perform integrative pathway analysis, such as multi-omics analysis. (4) Extract relevant genes that drive pathway significance as well as data corresponding to these relevant genes for additional in-depth analysis. (5) Perform analyses with enhanced computational efficiency with parallel computing and enhanced data safety with S4-class data objects. (6) Analyze studies with complex experimental designs, with multiple covariates, and with interaction effects, e.g., testing whether pathway association with clinical phenotype is different between male and female subjects. Citations: Chen et al. (2008) <https://doi.org/10.1093/bioinformatics/btn458>; Chen et al. (2010) <https://doi.org/10.1002/gepi.20532>; and Chen (2011) <https://doi.org/10.2202/1544-6115.1697>.
Maintained by Gabriel Odom. Last updated 5 months ago.
copynumbervariationdnamethylationgeneexpressionsnptranscriptiongenepredictiongenesetenrichmentgenesignalinggenetargetgenomewideassociationgenomicvariationcellbiologyepigeneticsfunctionalgenomicsgeneticslipidomicsmetabolomicsproteomicssystemsbiologytranscriptomicsclassificationdimensionreductionfeatureextractionprincipalcomponentregressionsurvivalmultiplecomparisonpathways
2.3 match 11 stars 7.74 score 42 scripts
cran
lsm:Estimation of the log Likelihood of the Saturated Model
When the values of the outcome variable Y are either 0 or 1, the function lsm() calculates the estimation of the log likelihood in the saturated model. This model is characterized by Llinas (2006, ISSN:2389-8976) in section 2.3 through the assumptions 1 and 2. The function LogLik() works (almost perfectly) when the number of independent variables K is high, but for small K it calculates wrong values in some cases. For this reason, when Y is dichotomous and the data are grouped in J populations, it is recommended to use the function lsm() because it works very well for all K.
Maintained by Jorge Villalba. Last updated 9 months ago.
6.6 match 2.48 score
business-science
tidyquant:Tidy Quantitative Financial Analysis
Bringing business and financial analysis to the 'tidyverse'. The 'tidyquant' package provides a convenient wrapper to various 'xts', 'zoo', 'quantmod', 'TTR' and 'PerformanceAnalytics' package functions and returns the objects in the tidy 'tibble' format. The main advantage is being able to use quantitative functions with the 'tidyverse' functions including 'purrr', 'dplyr', 'tidyr', 'ggplot2', 'lubridate', etc. See the 'tidyquant' website for more information, documentation and examples.
Maintained by Matt Dancho. Last updated 1 months ago.
dplyrfinancial-analysisfinancial-datafinancial-statementsmultiple-stocksperformance-analysisperformanceanalyticsquantmodstockstock-exchangesstock-indexesstock-listsstock-performancestock-pricesstock-symboltidyversetime-seriestimeseriesxts
1.2 match 872 stars 13.34 score 5.2k scripts
dyfanjones
noctua:Connect to 'AWS Athena' using R 'AWS SDK' 'paws' ('DBI' Interface)
Designed to be compatible with the 'R' package 'DBI' (Database Interface) when connecting to Amazon Web Service ('AWS') Athena <https://aws.amazon.com/athena/>. To do this the 'R' 'AWS' Software Development Kit ('SDK') 'paws' <https://github.com/paws-r/paws> is used as a driver.
Maintained by Dyfan Jones. Last updated 11 months ago.
1.5 match 46 stars 7.48 score 58 scripts
liamdbailey
climwin:Climate Window Analysis
Contains functions to detect and visualise periods of climate sensitivity (climate windows) for a given biological response. Please see van de Pol et al. (2016) <doi:10.1111/2041-210X.12590> and Bailey and van de Pol (2016) <doi:10.1371/journal.pone.0167980> for details.
Maintained by Liam D. Bailey. Last updated 5 years ago.
1.5 match 12 stars 7.42 score 138 scriptsdyfanjones
RAthena:Connect to 'AWS Athena' using 'Boto3' ('DBI' Interface)
Designed to be compatible with the R package 'DBI' (Database Interface) when connecting to Amazon Web Service ('AWS') Athena <https://aws.amazon.com/athena/>. To do this 'Python' 'Boto3' Software Development Kit ('SDK') <https://boto3.amazonaws.com/v1/documentation/api/latest/index.html> is used as a driver.
Maintained by Dyfan Jones. Last updated 1 years ago.
1.5 match 37 stars 7.10 score 38 scripts
z267xu
loon.tourr:Tour in 'Loon'
Implement tour algorithms in interactive graphical system 'loon'.
Maintained by Zehao Xu. Last updated 3 years ago.
2.2 match 4.48 score 6 scripts 1 dependents
gangwug
MetaCycle:Evaluate Periodicity in Large Scale Data
There are two functions-meta2d and meta3d for detecting rhythmic signals from time-series datasets. For analyzing time-series datasets without individual information, 'meta2d' is suggested, which could incorporates multiple methods from ARSER, JTK_CYCLE and Lomb-Scargle in the detection of interested rhythms. For analyzing time-series datasets with individual information, 'meta3d' is suggested, which takes use of any one of these three methods to analyze time-series data individual by individual and gives out integrated values based on analysis result of each individual.
Maintained by Gang Wu. Last updated 2 years ago.
1.3 match 26 stars 7.60 score 51 scripts 1 dependentscran
bda:Binned Data Analysis
Algorithms developed for binned data analysis, gene expression data analysis and measurement error models for ordinal data analysis.
Maintained by Bin Wang. Last updated 7 months ago.
3.6 match 2.61 score 82 scripts
isubirana
ImportExport:Import and Export Data
Import and export data from the most common statistical formats by using R functions that guarantee the least loss of the data information, giving special attention to the date variables and the labelled ones.
Maintained by Isaac Subirana. Last updated 4 years ago.
1.8 match 1.45 score 28 scripts