Provides the Scale class and corresponding functions, in order to facilitate data input for scale construction. Reverse items and alternative orders of administration are dealt with by the program. Computes reliability statistics, confirmatory, single factor loadings. It suggests item deletions and produces basic text output in English, for incorporation in reports. Returns list objects of all relevant functions from other packages (see Depends).

c(person(given = "Niloy",
family = "Biswas",
role = c("aut", "cre"),
email = "niloy_biswas@g.harvard.edu",
comment = c(ORCID = "0000-0001-9081-5702")),
person(given = "Lester",
family = "Mackey",
role = "aut"),
person(given = "Xiao-Li",
family = "Meng",
role = "aut"))
A scalable Gibbs sampling implementation for high dimensional Bayesian regression with the continuous spike-and-slab prior. Niloy Biswas, Lester Mackey and Xiao-Li Meng, "Scalable Spike-and-Slab" (2022) <arXiv:2204.01668>.
Niloy Biswas [aut, cre] (<https://orcid.org/0000-0001-9081-5702>),
Lester Mackey [aut],
Xiao-Li Meng [aut]

c(person("Chris", "Charlton", role=c("aut", "cre"), email="c.charlton@bristol.ac.uk"),
person("Harvey", "Goldstein", role="aut", email="H.Goldstein@bristol.ac.uk"))
Chris Charlton [aut, cre],
Harvey Goldstein [aut]
Perform a 'probabilistic' linkage of two data files using a scaling procedure using the methods described in Goldstein, H., Harron, K. and Cortina-Borja, M. (2017) <doi:10.1002/sim.7287>.

person("Michael", "North", email = "north@anl.gov", role = c("aut", "cre"))
Provides schema-on-read tools including a single function call (e.g., schemaOnRead("filename")) that reads text ('TXT'), comma separated value ('CSV'), raster image ('BMP', 'PNG', 'GIF', 'TIFF', and 'JPG'), R data ('RDS'), HDF5, NetCDF, spreadsheet ('XLS', 'XLSX', 'ODS', and 'DIF'), Weka Attribute-Relation File Format ('ARFF'), Epi Info ('REC'), SPSS ('SAV'), Systat ('SYS'), and Stata ('DTA') files. It also recursively reads folders (e.g., schemaOnRead("folder")), returning a nested list of the contained elements.