Showing 35 of total 35 results (show query)
brry
rdwd:Select and Download Climate Data from 'DWD' (German Weather Service)
Handle climate data from the 'DWD' ('Deutscher Wetterdienst', see <https://www.dwd.de/EN/climate_environment/cdc/cdc_node_en.html> for more information). Choose observational time series from meteorological stations with 'selectDWD()'. Find raster data from radar and interpolation according to <https://bookdown.org/brry/rdwd/raster-data.html>. Download (multiple) data sets with progress bars and no re-downloads through 'dataDWD()'. Read both tabular observational data and binary gridded datasets with 'readDWD()'.
Maintained by Berry Boessenkool. Last updated 6 days ago.
22.9 match 73 stars 7.77 score 79 scriptsopenintrostat
openintro:Datasets and Supplemental Functions from 'OpenIntro' Textbooks and Labs
Supplemental functions and data for 'OpenIntro' resources, which includes open-source textbooks and resources for introductory statistics (<https://www.openintro.org/>). The package contains datasets used in our open-source textbooks along with custom plotting functions for reproducing book figures. Note that many functions and examples include color transparency; some plotting elements may not show up properly (or at all) when run in some versions of Windows operating system.
Maintained by Mine Çetinkaya-Rundel. Last updated 3 months ago.
11.1 match 240 stars 11.39 score 6.0k scriptskatilingban
paleta:Collection of Palettes, Themes, and Theme Components
A collection of palettes, themes, and theme components based on publicly available branding guidelines of various non-governmental organisations, government agencies, and United Nations units.
Maintained by Ernest Guevarra. Last updated 2 months ago.
24.6 match 2 stars 4.48 score 8 scriptskjhealy
covdata:COVID-19 Data
COVID-19 related data from the ECDC, the COVID-19 Tracking Project, the New York Times, the Human Mortality Database, and Apple. Packaged for R.
Maintained by Kieran Healy. Last updated 2 years ago.
17.8 match 83 stars 4.73 score 129 scriptsstefvanbuuren
AGD:Analysis of Growth Data
Tools for the analysis of growth data: to extract an LMS table from a gamlss object, to calculate the standard deviation scores and its inverse, and to superpose two wormplots from different models. The package contains a some varieties of reference tables, especially for The Netherlands.
Maintained by Stef van Buuren. Last updated 11 months ago.
anthropometrycdcdutchgrowthgrowth-chartslmswhoz-score
18.5 match 1 stars 4.38 score 48 scriptscarriedaymont
growthcleanr:Data Cleaner for Anthropometric Measurements
Identifies implausible anthropometric (e.g., height, weight) measurements in irregularly spaced longitudinal datasets, such as those from electronic health records.
Maintained by Carrie Daymont. Last updated 16 days ago.
9.3 match 14 stars 6.68 score 41 scripts 1 dependentscmu-delphi
epidatr:Client for Delphi's 'Epidata' API
The Delphi 'Epidata' API provides real-time access to epidemiological surveillance data for influenza, 'COVID-19', and other diseases for the USA at various geographical resolutions, both from official government sources such as the Center for Disease Control (CDC) and Google Trends and private partners such as Facebook and Change 'Healthcare'. It is built and maintained by the Carnegie Mellon University Delphi research group. To cite this API: David C. Farrow, Logan C. Brooks, Aaron 'Rumack', Ryan J. 'Tibshirani', 'Roni' 'Rosenfeld' (2015). Delphi 'Epidata' API. <https://github.com/cmu-delphi/delphi-epidata>.
Maintained by David Weber. Last updated 4 months ago.
9.6 match 5 stars 6.14 score 114 scriptsstatist7
sitar:Super Imposition by Translation and Rotation Growth Curve Analysis
Functions for fitting and plotting SITAR (Super Imposition by Translation And Rotation) growth curve models. SITAR is a shape-invariant model with a regression B-spline mean curve and subject-specific random effects on both the measurement and age scales. The model was first described by Lindstrom (1995) <doi:10.1002/sim.4780141807> and developed as the SITAR method by Cole et al (2010) <doi:10.1093/ije/dyq115>.
Maintained by Tim Cole. Last updated 2 months ago.
5.4 match 13 stars 8.69 score 58 scripts 3 dependentsbrendensm
CDCPLACES:Access the 'CDC PLACES' API
Allows users to seamlessly query several 'CDC PLACES' APIs (<https://data.cdc.gov/browse?q=PLACES%20&sortBy=relevance>) by geography, state, measure, and release year. This package also contains a function to explore the available measures for each release year.
Maintained by Brenden Smith. Last updated 1 months ago.
7.5 match 14 stars 4.91 score 13 scriptssmouksassi
coveffectsplot:Produce Forest Plots to Visualize Covariate Effects
Produce forest plots to visualize covariate effects using either the command line or an interactive 'Shiny' application.
Maintained by Samer Mouksassi. Last updated 1 months ago.
3.5 match 32 stars 7.86 score 40 scriptssilentspringinstitute
RNHANES:Facilitates Analysis of CDC NHANES Data
Tools for downloading and analyzing CDC NHANES data, with a focus on analytical laboratory data.
Maintained by Herb Susmann. Last updated 2 days ago.
3.5 match 77 stars 7.58 score 83 scriptsjazznbass
scan:Single-Case Data Analyses for Single and Multiple Baseline Designs
A collection of procedures for analysing, visualising, and managing single-case data. These include piecewise linear regression models, multilevel models, overlap indices ('PND', 'PEM', 'PAND', 'PET', 'tau-u', 'baseline corrected tau', 'CDC'), and randomization tests. Data preparation functions support outlier detection, handling missing values, scaling, and custom transformations. An export function helps to generate html, word, and latex tables in a publication friendly style. More details can be found in the online book 'Analyzing single-case data with R and scan', Juergen Wilbert (2025) <https://jazznbass.github.io/scan-Book/>.
Maintained by Juergen Wilbert. Last updated 15 days ago.
3.8 match 4 stars 6.42 score 62 scripts 1 dependentsropensci
quadkeyr:Generate Raster Images from QuadKey-Identified Datasets
A set of functions of increasing complexity allows users to (1) convert QuadKey-identified datasets, based on Microsoft's Bing Maps Tile System, into Simple Features data frames, (2) transform Simple Features data frames into rasters, and (3) process multiple Meta (Facebook) QuadKey-identified human mobility files directly into raster files. For more details, see D’Andrea et al. (2024) <doi:10.21105/joss.06500>.
Maintained by Florencia DAndrea. Last updated 4 days ago.
geospatialquadkeyrastertilemap
2.7 match 12 stars 5.64 score 7 scriptsreichlab
zoltr:Interface to the 'Zoltar' Forecast Repository API
'Zoltar' <https://www.zoltardata.com/> is a website that provides a repository of model forecast results in a standardized format and a central location. It supports storing, retrieving, comparing, and analyzing time series forecasts for prediction challenges of interest to the modeling community. This package provides functions for working with the 'Zoltar' API, including connecting and authenticating, getting meta information (projects, models, and forecasts, and truth), and uploading, downloading, and deleting forecast and truth data.
Maintained by Matthew Cornell. Last updated 10 days ago.
1.7 match 2 stars 7.58 score 175 scripts 3 dependentsnutriverse
zscorer:Child Anthropometry z-Score Calculator
A tool for calculating z-scores and centiles for weight-for-age, length/height-for-age, weight-for-length/height, BMI-for-age, head circumference-for-age, age circumference-for-age, subscapular skinfold-for-age, triceps skinfold-for-age based on the WHO Child Growth Standards.
Maintained by Ernest Guevarra. Last updated 4 years ago.
anthropometric-indicesanthropometrygrowth-chartsgrowth-standardsheight-for-agenutritionweight-for-ageweight-for-heightz-score
1.7 match 14 stars 7.30 score 47 scripts 1 dependentscran
SSDforR:Functions to Analyze Single System Data
Functions to visually and statistically analyze single system data.
Maintained by Charles Auerbach. Last updated 3 months ago.
6.7 match 1.48 scoremvogel78
childsds:Data and Methods Around Reference Values in Pediatrics
Calculation of standard deviation scores and percentiles adduced from different standards (WHO, UK, Germany, Italy, China, etc). Also, references for laboratory values in children and adults are available, e.g., serum lipids, iron-related blood parameters, IGF, liver enzymes. See package documentation for full list.
Maintained by Mandy Vogel. Last updated 2 months ago.
3.4 match 2.83 score 51 scriptsshihao-yang
argo:Accurate Estimation of Influenza Epidemics using Google Search Data
Augmented Regression with General Online data (ARGO) for accurate estimation of influenza epidemics in United States on national level, regional level and state level. It replicates the method introduced in paper Yang, S., Santillana, M. and Kou, S.C. (2015) <doi:10.1073/pnas.1515373112>; Ning, S., Yang, S. and Kou, S.C. (2019) <doi:10.1038/s41598-019-41559-6>; Yang, S., Ning, S. and Kou, S.C. (2021) <doi:10.1038/s41598-021-83084-5>.
Maintained by Shihao Yang. Last updated 2 years ago.
5.1 match 2 stars 1.30 score 7 scriptscdcgov
surveytable:Formatted Survey Estimates
Short and understandable commands that generate tabulated, formatted, and rounded survey estimates. Mostly a wrapper for the 'survey' package (Lumley (2004) <doi:10.18637/jss.v009.i08> <https://CRAN.R-project.org/package=survey>) that identifies low-precision estimates using the National Center for Health Statistics (NCHS) presentation standards (Parker et al. (2017) <https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf>, Parker et al. (2023) <doi:10.15620/cdc:124368>).
Maintained by Alex Strashny. Last updated 4 days ago.
estimatesformatted-outputpretty-printsurveytables
0.8 match 6 stars 6.71 score 19 scriptscjendres1
nhanesA:NHANES Data Retrieval
Utility to retrieve data from the National Health and Nutrition Examination Survey (NHANES) website <https://www.cdc.gov/nchs/nhanes/>.
Maintained by Christopher Endres. Last updated 2 months ago.
0.5 match 59 stars 9.37 score 239 scriptswencanhong
cdcsis:Conditional Distance Correlation Based Feature Screening and Conditional Independence Inference
Conditional distance correlation <doi:10.1080/01621459.2014.993081> is a novel conditional dependence measurement of two multivariate random variables given a confounding variable. This package provides conditional distance correlation, performs the conditional distance correlation sure independence screening procedure for ultrahigh dimensional data <https://www3.stat.sinica.edu.tw/statistica/J28N1/J28N114/J28N114.html>, and conducts conditional distance covariance test for conditional independence assumption of two multivariate variable.
Maintained by Canhong Wen. Last updated 7 months ago.
1.7 match 1 stars 2.88 score 25 scripts 1 dependentsheli-xu
findSVI:Calculate Social Vulnerability Index for Communities
Developed by CDC/ATSDR (Centers for Disease Control and Prevention/ Agency for Toxic Substances and Disease Registry), Social Vulnerability Index (SVI) serves as a tool to assess the resilience of communities by taking into account socioeconomic and demographic factors. Provided with year(s), region(s) and a geographic level of interest, 'findSVI' retrieves required variables from US census data and calculates SVI for communities in the specified area based on CDC/ATSDR SVI documentation. Reference for the calculation methods: Flanagan BE, Gregory EW, Hallisey EJ, Heitgerd JL, Lewis B (2011) <doi:10.2202/1547-7355.1792>.
Maintained by Heli Xu. Last updated 1 months ago.
0.8 match 12 stars 5.68 score 16 scriptsrsparapa
nftbart:Nonparametric Failure Time Bayesian Additive Regression Trees
Nonparametric Failure Time (NFT) Bayesian Additive Regression Trees (BART): Time-to-event Machine Learning with Heteroskedastic Bayesian Additive Regression Trees (HBART) and Low Information Omnibus (LIO) Dirichlet Process Mixtures (DPM). An NFT BART model is of the form Y = mu + f(x) + sd(x) E where functions f and sd have BART and HBART priors, respectively, while E is a nonparametric error distribution due to a DPM LIO prior hierarchy. See the following for a complete description of the model at <doi:10.1111/biom.13857>.
Maintained by Rodney Sparapani. Last updated 1 years ago.
3.6 match 1.15 score 14 scriptsbiostats-dev
ggsurveillance:Tools for Outbreak Investigation/Infectious Disease Surveillance
Create epicurves or epigantt charts in 'ggplot2'. Prepare data for visualisation or other reporting for infectious disease surveillance and outbreak investigation. Includes tidy functions to solve date based transformations for common reporting tasks, like (A) seasonal date alignment for respiratory disease surveillance, (B) date-based case binning based on specified time intervals like isoweek, epiweek, month and more, (C) automated detection and marking of the new year based on the date/datetime axis of the 'ggplot2'. An introduction on how to use epicurves can be found on the US CDC website (2012, <https://www.cdc.gov/training/quicklearns/epimode/index.html>).
Maintained by Alexander Bartel. Last updated 14 days ago.
epidemiologyinfectious-disease-surveillanceinfectious-diseasesoutbreaks
0.8 match 2 stars 5.31 scoredewittpe
pedbp:Pediatric Blood Pressure
Data and utilities for estimating pediatric blood pressure percentiles by sex, age, and optionally height (stature) as described in Martin et.al. (2022) <doi:10.1001/jamanetworkopen.2022.36918>. Blood pressure percentiles for children under one year of age come from Gemelli et.al. (1990) <doi:10.1007/BF02171556>. Estimates of blood pressure percentiles for children at least one year of age are informed by data from the National Heart, Lung, and Blood Institute (NHLBI) and the Centers for Disease Control and Prevention (CDC) <doi:10.1542/peds.2009-2107C> or from Lo et.al. (2013) <doi:10.1542/peds.2012-1292>. The flowchart for selecting the informing data source comes from Martin et.al. (2022) <doi:10.1542/hpeds.2021-005998>.
Maintained by Peter DeWitt. Last updated 2 months ago.
blood-pressuregrowth-standardspediatriccpp
0.5 match 6 stars 6.43 score 45 scriptsjhchou
peditools:Pediatric Clinical Data Science Tools
A collection of tools for newborn and pediatric anthropometric calculations and data abstraction from Vermont Oxford Network registry exports. Includes charts based on Lambda, Mu, Sigma (LMS) parameters, including: Fenton 2003, Olsen 2010, Olsen BMI, CDC infant, CDC pediatric, CDC BMI, CDC (Addo) skin, WHO infant, WHO skin, Abdel-Rahman 2017, Mramba 2017, Zemel Down Syndrome, Brooks cerebral palsy, WHO expanded, Cappa 2024 (except BMI). Includes functions to take a Vermont Oxford Network XML or CSV data file export read into a data frame, converting the coded variables into human readable factors.
Maintained by Joseph Chou. Last updated 2 months ago.
1.0 match 5 stars 3.00 score 2 scriptsrpruim
NHANES:Data from the US National Health and Nutrition Examination Study
Body Shape and related measurements from the US National Health and Nutrition Examination Survey (NHANES, 1999-2004). See http://www.cdc.gov/nchs/nhanes.htm for details.
Maintained by Randall Pruim. Last updated 10 years ago.
0.5 match 5.20 score 880 scriptsgshs-ornl
revengc:Reverse Engineering Summarized Data
Decoupled (e.g. separate averages) and censored (e.g. > 100 species) variables are continually reported by many well-established organizations (e.g. World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), World Bank, and various national censuses). The challenge therefore is to infer what the original data could have been given summarized information. We present an R package that reverse engineers decoupled and/or censored count data with two main functions. The cnbinom.pars() function estimates the average and dispersion parameter of a censored univariate frequency table. The rec() function reverse engineers summarized data into an uncensored bivariate table of probabilities.
Maintained by Samantha Duchscherer. Last updated 6 years ago.
0.5 match 5 stars 3.44 score 11 scripts