View source: R/createDiscreteCovariates.R
createDiscreteCovariates | R Documentation |
The values
and probs
argument are parsed using the
parseHashString
helper function. They could be either :
a vector giving the values for each variable.
c("1,2", "1,2,3")
would mean that the first variable takes values
1 and 2, and the second variable takes values 1, 2 and 3.
a list giving the values for each variable.
list(c(1,2), c(1,2,3))
would mean that the first variable takes
values 1 and 2, and the second variable takes values 1, 2 and 3.
a compact notation using the hash symbol to separate variables
"1,2#1,2,3"
createDiscreteCovariates(
subjects,
names,
values,
probs,
probArray,
seed = .deriveFromMasterSeed(),
idCol = getEctdColName("Subject"),
includeIDCol = TRUE
)
subjects |
(Required) Vector of subjects (or number of subjects) for which to create covariates |
names |
(Required) Names of the discrete covariates to be created. All
the names should be valid R names. See |
values |
(Required) Values that the covariates can take. See details section. |
probs |
(Optional) Probabilities for each covariates. See details section. |
probArray |
(Optional) Probability array for uneven sampling. See details section. |
seed |
(Optional) Random seed to use.By default, it is based on the current random seed |
idCol |
(Optional) Name of the subject column. Must be a valid R name
(see |
includeIDCol |
(Optional) A logical value. Should the subject column be |
Additionally for the probs
argument, a check is performed to make
sure that each variable probability sums to 1.
Alternatively, a probArray
argument can be given. This should be a
data frame containing one more column (named "prob") than the number of
variables to create. Each variable has a column which contains the values it
can take. The prob column gives the probability for each combination. See
examples. The prob column should sum up to one.
A data frame.
createContinuousCovariates
,
# 10 samples of X and Y where:
# P[ X = 1 ] = .1
# P[ X = 2 ] = .9
# -
# P[ Y = 7 ] = .5
# P[ Y = 8 ] = .4
# P[ Y = 9 ] = .1
createDiscreteCovariates( 10 ,
names = "X, Y",
probs = ".1,.9#.5,.4,.1",
values = "1,2#7,8,9")
# using the probArray version
pa <- data.frame( F1 = rep(0:1, 3),
F2 = rep(1:3, each = 2),
PROB = c(.1,.2,.1,.2,.2,.2) )
createDiscreteCovariates( 100 , probArray = pa )
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.