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Indices of Effect Size
Provide utilities to work with indices of effect size for a wide
variety of models and hypothesis tests (see list of supported models using
the function 'insight::supported_models()'), allowing computation of and
conversion between indices such as Cohen's d, r, odds, etc.
References: Ben-Shachar et al. (2020)
Statistical Analysis in Epidemiology
Functions for demographic and epidemiological analysis in the Lexis diagram, i.e. register and cohort follow-up data. In particular representation, manipulation, rate estimation and simulation for multistate data - the Lexis suite of functions, which includes interfaces to 'mstate', 'etm' and 'cmprsk' packages. Contains functions for Age-Period-Cohort and Lee-Carter modeling and a function for interval censored data. Has functions for extracting and manipulating parameter estimates and predicted values (ci.lin and its cousins), as well as a number of epidemiological data sets.
Regression with Functional Data
Methods for regression for functional data, including function-on-scalar, scalar-on-function, and function-on-function regression. Some of the functions are applicable to image data.
Distributed Lag Non-Linear Models
Collection of functions for distributed lag linear and non-linear models.
Tidying Methods for Mixed Models
Convert fitted objects from various R mixed-model packages into tidy data frames along the lines of the 'broom' package. The package provides three S3 generics for each model: tidy(), which summarizes a model's statistical findings such as coefficients of a regression; augment(), which adds columns to the original data such as predictions, residuals and cluster assignments; and glance(), which provides a one-row summary of model-level statistics.
Convert Statistical Objects into Tidy Tibbles
Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.
Time Series Analysis
Contains R functions and datasets detailed in the book "Time Series Analysis with Applications in R (second edition)" by Jonathan Cryer and Kung-Sik Chan.
R Commander
A platform-independent basic-statistics GUI (graphical user interface) for R, based on the tcltk package.
Forecasting Mortality, Fertility, Migration and Population Data
Functions for demographic analysis including lifetable calculations; Lee-Carter modelling; functional data analysis of mortality rates, fertility rates, net migration numbers; and stochastic population forecasting.
SIMEX- And MCSIMEX-Algorithm for Measurement Error Models
Implementation of the SIMEX-Algorithm by Cook & Stefanski (1994)