cut_rhemtulla: Convert normal data to item scale
In julianhatwell/arulesimp: Association Rules Based Method for Imputation
Description
Simulate Likert scales and ordinal data by discretizing normally distributed
data based on desired distribution and number of levels.
Usage
1
cut_rhemtulla(dt, dist = "symmetric", levs = 5, labels = FALSE)
Arguments
dt
A data frame.
dist
A character string. Allowed values are "symmetric"
"moderate_asym" and "severe_asym" to select the desired distribution.
Default = "symmetric"
levs
A scalar integer to set the number of item levels.
Allowed values are 2, 3, 5 or 7.
labels
A scalar boolean. Passed to the cut function.
Determines whether labels or underlying factor keys are returned.
Default = FALSE
julianhatwell/arulesimp documentation built on May 11, 2019, 4:17 p.m.
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Description
Simulate Likert scales and ordinal data by discretizing normally distributed data based on desired distribution and number of levels.
Usage
1 | cut_rhemtulla(dt, dist = "symmetric", levs = 5, labels = FALSE)
|
Arguments
dt |
A data frame. |
dist |
A character string. Allowed values are "symmetric" "moderate_asym" and "severe_asym" to select the desired distribution. Default = "symmetric" |
levs |
A scalar integer to set the number of item levels. Allowed values are 2, 3, 5 or 7. |
labels |
A scalar boolean. Passed to the cut function.
Determines whether labels or underlying factor keys are returned.
Default = |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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