This package includes several functions to study multigroup data,
where the same set of variables are measured on different groups of
individuals.

Several functions are presented in order to study data in a group structure,
where the same set of variables are measured on different groups of
individuals.

Multivariate analysis methods including principal component analysis,
partial least square regression, and multiblock analysis to describe,
summarize, and visualize data with a group structure.

Generalised Function to Calculate a Variety of Multilateral
Price Index Methods
c(person("Matthew", "Stansfield",
email = "m.stansfield85@gmail.com",
role = c("aut", "cre")))
A flexible, efficient implementation of multilateral price index calculations.
Includes common methods focused on time product dummy regression and GEKS variations.
Allows for extension of the methods through automatic window splicing.
See Krsinich (2016) <doi: 10.1515/jos-2016-0021>.
testthat, knitr, rmarkdown, devtools, dplyr, ggplot2
assertive, data.table, fastmatch, parallel, yaml, MatrixModels

Transitive Index Numbers for Cross-Sections and Panel Data
Computing transitive (and non-transitive) index numbers (Coelli et al., 2005 <doi:10.1007/b136381>) for cross-sections and panel data. For the calculation of transitive indexes, the EKS (Coelli et al., 2005 <doi:10.1007/b136381>; Rao et al., 2002 <doi:10.1007/978-1-4615-0851-9_4>) and Minimum spanning tree (Hill, 2004 <doi:10.1257/0002828043052178>) methods are implemented. Traditional fixed-base and chained indexes, and their growth rates, can also be derived using the Paasche, Laspeyres, Fisher and Tornqvist formulas.

The functions in this package are designed to be used in the analysis of multilevel data by organizational and social psychologists.  The package includes a number of estimates of within-group agreement, and a series of routines using random group resampling (RGR) to identify the group-level properties of data.  Finally, the package contains some basic simple routines for estimating reliability.