No packages match

datefixR - Standardize Dates in Different Formats or with Missing Data

There are many different formats dates are commonly represented with: the order of day, month, or year can differ, different separators ("-", "/", or whitespace) can be used, months can be numerical, names, or abbreviations and year given as two digits or four. 'datefixR' takes dates in all these different formats and converts them to R's built-in date class. If 'datefixR' cannot standardize a date, such as because it is too malformed, then the user is told which date cannot be standardized and the corresponding ID for the row. 'datefixR' also allows the imputation of missing days and months with user-controlled behavior.

Last updated

dateswranglingrustcargo

8.24 score 33 stars 49 scripts 713 downloads

datefixR - Standardize Dates in Different Formats or with Missing Data

There are many different formats dates are commonly represented with: the order of day, month, or year can differ, different separators ("-", "/", or whitespace) can be used, months can be numerical, names, or abbreviations and year given as two digits or four. 'datefixR' takes dates in all these different formats and converts them to R's built-in date class. If 'datefixR' cannot standardize a date, such as because it is too malformed, then the user is told which date cannot be standardized and the corresponding ID for the row. 'datefixR' also allows the imputation of missing days and months with user-controlled behavior.

Last updated

dateswranglingrustcargo

8.24 score 33 stars 49 scripts 771 downloads

landmaRk - Time-to-Event Landmark Analysis using an Array of Longitudinal and Survival Sub-Models

Provides a modular end-to-end framework for dynamic risk prediction based on time-to-event and longitudinal data. This allows flexible specifications for the longitudinal and survival sub-models. The 'landmaRk' package enables reproducible benchmarks of different model choices, including cross-validation to assess out-of-sample predictive performance. Methods are described in Velasco-Pardo, Constantine-Cooke, Lees and Vallejos (2026, manuscript under preparation) 'Landmarking with Latent Class Mixed Models for Dynamic Prediction of Time-to-event Data with Heterogeneous Biomarker Trajectories'.

Last updated

landmarkinglongitudinal-datasurvival-analysistime-to-event

5.64 score 1 stars 10 scripts 465 downloads

gameR - Color Palettes Inspired by Video Games

Palettes based on video games.

Last updated

gamingggplot2palettes

5.44 score 6 stars 23 scripts 267 downloads

BASSLINE - Bayesian Survival Analysis Using Shape Mixtures of Log-Normal Distributions

Mixtures of life distributions provide a convenient framework for survival analysis: particularly when standard models such as the Weibull are unable to capture some features from the data. These mixtures can also account for unobserved heterogeneity or outlying observations. BASSLINE uses shape mixtures of log-normal distributions and has particular applicability to data with fat tails.

Last updated

openblascpp

2.70 score

libdr - Support Functions used by the LIBDR LCMM Analysis

This package provides support functions frequently used by Constantine et al. for their paper, "Large-scale clustering of longitudinal faecal calprotectin and C-reactive protein profiles in inflammatory bowel disease". These functions are primarily used to manipulate data and visualise findings.

Last updated

clusteringcrpdenmarkfcalibdlcmmscotland

2.23 score 17 scripts

libdr - Support Functions used by the LIBDR LCMM Analysis

This package provides support functions frequently used by Constantine et al. for their paper, "Large-scale clustering of longitudinal faecal calprotectin and C-reactive protein profiles in inflammatory bowel disease". These functions are primarily used to manipulate data and visualise findings.

Last updated

clusteringcrpdenmarkfcalibdlcmmscotland

2.23 score 17 scripts