Showing 6 of total 6 results (show query)
mayoverse
arsenal:An Arsenal of 'R' Functions for Large-Scale Statistical Summaries
An Arsenal of 'R' functions for large-scale statistical summaries, which are streamlined to work within the latest reporting tools in 'R' and 'RStudio' and which use formulas and versatile summary statistics for summary tables and models. The primary functions include tableby(), a Table-1-like summary of multiple variable types 'by' the levels of one or more categorical variables; paired(), a Table-1-like summary of multiple variable types paired across two time points; modelsum(), which performs simple model fits on one or more endpoints for many variables (univariate or adjusted for covariates); freqlist(), a powerful frequency table across many categorical variables; comparedf(), a function for comparing data.frames; and write2(), a function to output tables to a document.
Maintained by Ethan Heinzen. Last updated 8 months ago.
baseline-characteristicsdescriptive-statisticsmodelingpaired-comparisonsreportingstatisticstableone
225 stars 13.40 score 1.2k scripts 15 dependents
gpaux
Mediana:Clinical Trial Simulations
Provides a general framework for clinical trial simulations based on the Clinical Scenario Evaluation (CSE) approach. The package supports a broad class of data models (including clinical trials with continuous, binary, survival-type and count-type endpoints as well as multivariate outcomes that are based on combinations of different endpoints), analysis strategies and commonly used evaluation criteria.
Maintained by Gautier Paux. Last updated 4 years ago.
biostatisticsclinical-trial-simulationsclinical-trialssimulations
29 stars 6.53 score 39 scripts
jeff-hughes
paramtest:Run a Function Iteratively While Varying Parameters
Run simulations or other functions while easily varying parameters from one iteration to the next. Some common use cases would be grid search for machine learning algorithms, running sets of simulations (e.g., estimating statistical power for complex models), or bootstrapping under various conditions. See the 'paramtest' documentation for more information and examples.
Maintained by Jeffrey Hughes. Last updated 5 days ago.
1 stars 4.85 score 47 scripts
jiahui1902
APCI:A New Age-Period-Cohort Model for Describing and Investigating Inter-Cohort Differences and Life Course Dynamics
It implemented Age-Period-Interaction Model (APC-I Model) proposed in the paper of Liying Luo and James S. Hodges in 2019. A new age-period-cohort model for describing and investigating inter-cohort differences and life course dynamics.
Maintained by Jiahui Xu. Last updated 7 months ago.
3 stars 2.48 score 3 scripts
cran
NiLeDAM:Monazite Dating for the NiLeDAM Team
Th-U-Pb electron microprobe age dating of monazite, as originally described in <doi:10.1016/0009-2541(96)00024-1>.
Maintained by Nathalie Vialaneix. Last updated 2 years ago.
2.00 score
djpedregal
UComp:Automatic Univariate Time Series Modelling of many Kinds
Comprehensive analysis and forecasting of univariate time series using automatic time series models of many kinds. Harvey AC (1989) <doi:10.1017/CBO9781107049994>. Pedregal DJ and Young PC (2002) <doi:10.1002/9780470996430>. Durbin J and Koopman SJ (2012) <doi:10.1093/acprof:oso/9780199641178.001.0001>. Hyndman RJ, Koehler AB, Ord JK, and Snyder RD (2008) <doi:10.1007/978-3-540-71918-2>. Gómez V, Maravall A (2000) <doi:10.1002/9781118032978>. Pedregal DJ, Trapero JR and Holgado E (2024) <doi:10.1016/j.ijforecast.2023.09.004>.
Maintained by Diego J. Pedregal. Last updated 30 days ago.
1 stars 1.70 score 1 scripts