c(person(given = "Derek W.",
family = "Brown",
role = c("aut", "cre"),
email = "derek.brown@nih.gov"),
person(given = "Mitchel J.",
family = "Machiela",
role = "aut",
email = "mitchell.machiela@nih.gov"),
person(given = "Timothy A.",
family = "Myers",
role = "ctb",
email = "myersta@mail.nih.gov"),
person(given = "NCI",
role = c("cph", "fnd")))
Matches cases to controls based on genotype principal components (PC).
In order to produce better results, matches are based on the weighted
distance of PCs where the weights are equal to the % variance explained
by that PC. A weighted Mahalanobis distance metric (Kidd et al. (1987)
<DOI:10.1016/0031-3203(87)90066-5>) is used to determine matches.

c(person(given = "Derek W.",
family = "Brown",
role = c("aut", "cre"),
email = "derek.brown@nih.gov",
comment = c(ORCID = "0000-0001-8393-1713")),
person(given = "Mitchel J.",
family = "Machiela",
role = "aut",
email = "mitchell.machiela@nih.gov",
comment = c(ORCID = "0000-0001-6538-9705")),
person(given = "Timothy A.",
family = "Myers",
role = "ctb",
email = "myersta@mail.nih.gov",
comment = c(ORCID = "0000-0001-8127-3446")),
person(given = "NCI",
role = c("cph", "fnd")))
optmatch, testthat, knitr, rmarkdown, R.rsp
Derek W. Brown [aut, cre] (<https://orcid.org/0000-0001-8393-1713>),
Mitchel J. Machiela [aut] (<https://orcid.org/0000-0001-6538-9705>),
Timothy A. Myers [ctb] (<https://orcid.org/0000-0001-8127-3446>),
NCI [cph, fnd]

c(person(given = "Derek W.",
family = "Brown",
role = c("aut", "cre"),
email = "derek9@gwmail.gwu.edu",
comment = c(ORCID = "0000-0001-8393-1713")),
person(given = "Mitchel J.",
family = "Machiela",
role = "aut",
email = "mitchell.machiela@nih.gov",
comment = c(ORCID = "0000-0001-6538-9705")),
person(given = "Timothy A.",
family = "Myers",
role = "ctb",
email = "myersta@mail.nih.gov",
comment = c(ORCID = "0000-0001-8127-3446")),
person(given = "NCI",
role = c("cph", "fnd")))

Multivariate analysis for a mixture of quantitative and
qualitative data
Marie Chavent and Vanessa Kuentz and Amaury Labenne and Benoit Liquet and Jerome Saracco
Principal Component Analysis, orthogonal rotation and multiple factor
analysis for a mixture of quantitative and qualitative variables.
'PCAmix.R' 'PCArot.R' 'plot.PCAmix.R' 'predict.PCAmix.R'
'print.PCAmix.R' 'recod.R' 'recodqual.R' 'recodquant.R'
'sol.2dim.R' 'summary.PCAmix.R' 'tab.disjonctif.NA.R'
'svd.triplet.R' 'Cut.Group.R' 'nb.level.R' 'Tri.Data.R'
'Lg.pond.R' 'Lg.R' 'RV.R' 'RV.pond.R' 'MFAmix.R'
'plot.MFAmix.R' 'print.MFAmix.R' 'summary.MFAmix.R'