stringr, data.table, reshape2, rlang, stats, lme4, nlme,
flexsurv, survminer, SurvRegCensCov, survival, MASS, systemfit,
IPDFileCheck, valueEQ5D, car, ggplot2, grDevices, lmtest,
broom, effects, gvlma, methods, relaimpo, tm

readxl, stringr, data.table, reshape2, rlang, stats, lme4,
nlme, flexsurv, survminer, SurvRegCensCov, survival, MASS,
systemfit, IPDFileCheck, valueEQ5D, car, ggplot2, grDevices,
lmtest, broom, effects, gvlma, methods, relaimpo, tm,
tidyverse, tibble, dplyr, tidyr, hash
ISLR, foreign, knitr, rmarkdown, covr, testthat

A collection of functions to construct Markov model for model-based
cost-effectiveness analysis. This includes creating Markov model (both time
homogenous and time dependent models), decision analysis, sensitivity
analysis (deterministic and probabilistic). The package allows estimation
of parameters for the Markov model from a given individual patient level
data, provided the data file follows some standard data entry rules.

readxl, stringr, data.table, reshape2, rlang, stats, lme4,
nlme, flexsurv, survminer, SurvRegCensCov, survival, MASS,
systemfit, IPDFileCheck, valueEQ5D, car, ggplot2, grDevices,
lmtest, broom, effects, gvlma, methods, relaimpo, tm,
tidyverse, tibble, dplyr, tidyr, hash, haven

A few useful functions for statisticians
Various useful functions for statisticians

Various useful functions for statisticians: describe data,
plot Kaplan-Meier curves with numbers of subjects at risk,
compare data sets, display spaghetti-plot, build
multi-contingency tables...

Various useful functions for statisticians: describe data, plot Kaplan-Meier curves with numbers of subjects at risk, compare data sets, display spaghetti-plot, build multi-contingency tables...

A few Useful Functions for Statisticians

Multi-Block Partial Least Squares Discriminant Analysis
Marion Brandolini-Bunlon, Stephanie Bougeard, Melanie Petera, Estelle Pujos-Guillot
Several functions are provided to implement a MBPLSDA : components search, optimal model components number search, optimal model validity test by permutation tests, observed values evaluation of optimal model parameters and predicted categories, bootstrap values evaluation of optimal model parameters and predicted cross-validated categories. The use of this package is described in Brandolini-Bunlon et al (2019, Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data (submitted in Metabolomics)).
DiscriMiner, MASS, parallel, doParallel, foreach, FactoMineR