Estimate Entry Models

Tools for measuring empirically the effects of entry in concentrated markets, based in Bresnahan and Reiss (1991) < https://www.jstor.org/stable/2937655>.

Generalized Efficient Regression-Based Imputation with Latent Processes

Implements a new multiple imputation method that draws imputations from a latent joint multivariate normal model which underpins generally structured data. This model is constructed using a sequence of flexible conditional linear models that enables the resulting procedure to be efficiently implemented on high dimensional datasets in practice. See Robbins (2021) .

Specification Tests for Parametric Propensity Score Models

The propensity score is one of the most widely used tools in studying the causal effect of a treatment, intervention, or policy. Given that the propensity score is usually unknown, it has to be estimated, implying that the reliability of many treatment effect estimators depends on the correct specification of the (parametric) propensity score. This package implements the data-driven nonparametric diagnostic tools for detecting propensity score misspecification proposed by Sant'Anna and Song (2019) .

Gene Set Enrichment Meta-Analysis

Performing the different steps of gene set enrichment meta-analysis. It provides different functions that allow the application of meta-analysis based on the combination of effect sizes from different pathways in different studies to obtain significant pathways that are common to all of them.

Measure of Agreement Between Two Raters

Measure of agreement delta was originally by Martín & Femia (2004) . Since then has been considered as agreement measure for different fields, since their behavior is usually better than the usual kappa index by Cohen (1960) . The main issue with delta is that can not be computed by hand contrary to kappa. The current algorithm is based on the Version 5 of the delta windows program that can be found on < https://www.ugr.es/~bioest/software/delta/cmd.php?seccion=downloads>.

Bimodal Gumbel Distribution

Bimodal Gumbel distribution. General functions for performing extreme value analysis.

Converting Transport Data from GTFS Format to GPS-Like Records

Convert general transit feed specification (GTFS) data to global positioning system (GPS) records in 'data.table' format. It also has some functions to subset GTFS data in time and space and to convert both representations to simple feature format.

Generate Sample Censoring

Provides functions to generate censored samples of type I, II and III, from any random sample generator. It also supplies the option to create left and right censorship. Along with this, the generation of samples with interval censoring is in the testing phase, with two options of fixed length intervals and random lengths.

Build Network Based on Linear Mixed Models from EHRs

Analyzing longitudinal clinical data from Electronic Health Records (EHRs) using linear mixed models (LMM) and visualizing the results as networks. It includes functions for fitting LMM, normalizing adjacency matrices, and comparing networks. The package is designed for researchers in clinical and biomedical fields who need to model longitudinal data and explore relationships between variables For more details see Bates et al. (2015) .

Extra Features for 'reactable' Package

Enhanced functionality for 'reactable' in 'shiny' applications, offering interactive and dynamic data table capabilities with ease. With 'reactable.extras', easily integrate a range of functions and components to enrich your 'shiny' apps and facilitate user-friendly data exploration.