modifyPropsContinuous | R Documentation |
Runs modifyProps on a continuous variable Takes a continuous variable, converts it to a categorical variable using the binbreaks, modifyProps is then called on that categorical variable. The categorical variable is then converted back to a continuos variable using the catToContModels
modifyPropsContinuous(
x.cont,
desired_props,
catToContModels,
cont.binbreaks,
propens = NULL,
logiset = NULL,
accuracy = 0.01,
envir = parent.frame()
)
x.cont |
a continuous variable to be adjusted |
desired_props |
desired proportions |
catToContModels |
a list of models which will to used to convert the adjusted categorical variable back to continuous |
cont.binbreaks |
binbreaks for the continuous variable to be adjusted |
propens |
matrix or vector of the propensity scores for each child For binary variables there is one column of propensity scores: the propensities to change from a 0 to a 1. For categorical variables with more than two categories there are multiple columns of propensity scores: E.g. for a three category variables the propensities to change from category 1 to category 2 are in the first column and the propensities to change from category 2 to category 3 are in the second column. |
logiset |
logical vector indicating which observations to include, or NULL to include all. |
accuracy |
gives how close the end proportions are allowed to be away from the desired proportions before an error message is given - the default is 0.01. If the '.accuracy' global variable exists, its value will be used instead of that in function call. |
envir |
environment in which to evaluate model variables. |
an 'adjusted' continuous variable that if binned will have the same proportions as requested in desired_props
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