cmat | R Documentation |
Use these functions to retrieve or set a hypr
object’s contrast matrix. If used for updating, the hypothesis matrix and equations are derived automatically.
cmat(x, add_intercept = FALSE, remove_intercept = FALSE, as_fractions = TRUE)
cmat(x, add_intercept = FALSE, remove_intercept = FALSE) <- value
contr.hypothesis(
...,
add_intercept = FALSE,
remove_intercept = NULL,
as_fractions = FALSE
)
## S4 replacement method for signature 'factor,ANY,hypr'
contrasts(x, how.many = NULL) <- value
## S4 replacement method for signature 'factor,ANY,hypr_cmat'
contrasts(x, how.many = NULL) <- value
contr.hypothesis(
x,
add_intercept = NULL,
remove_intercept = FALSE,
as_fractions = FALSE
) <- value
x |
A hypr object |
add_intercept |
Add additional intercept column to contrast matrix |
remove_intercept |
If |
as_fractions |
Should the returned matrix be formatted as fractions (using |
value |
contrast matrix |
... |
A list of hypothesis equations for which to retrieve a contrast matrix |
how.many |
see |
Basic specification of contrasts in R is accomplished with basic R functions stats::contrasts()
and stats::C()
(Chambers & Hastie, 1992). Other relevant packages for this topic are multcomp
(Bretz et al., 2010), contrast
(Kuhn et al., 2016), and, including also various vignettes, emmeans
(Lenth, 2019).
A matrix
of contrast codes with contrasts as columns and levels as rows.
cmat(x, add_intercept = FALSE, remove_intercept = FALSE) <- value
: Set contrast matrix
contr.hypothesis()
: Retrieve contrast matrix with sensible intercept default to override factor contrasts
contrasts(x = factor, how.many = ANY) <- value
: Update factor contrasts
contrasts(x = factor, how.many = ANY) <- value
: Update factor contrasts
contr.hypothesis(
x,
add_intercept = NULL,
remove_intercept = FALSE,
as_fractions = FALSE
) <- value
: Update contrast matrix with sensible intercept default
Chambers, J. M. and Hastie, T. J. (1992) Statistical models. Chapter 2 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.
Frank Bretz, Torsten Hothorn and Peter Westfall (2010), Multiple Comparisons Using R, CRC Press, Boca Raton.
Max Kuhn, contributions from Steve Weston, Jed Wing, James Forester and Thorn Thaler (2016). contrast: A Collection of Contrast Methods. R package version 0.21. https://CRAN.R-project.org/package=contrast
Lenth, R. (2019). emmeans: Estimated Marginal Means, aka Least-Squares Means. R package version 1.4.1. https://CRAN.R-project.org/package=emmeans
hypr
h <- hypr(mu1~0, mu2~mu1)
cmat(h) # retrieve the contrast matrix
contr.hypothesis(h) # by default without intercept (removes first column)
contr.hypothesis(mu1~0, mu2~mu1)
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