Gets data needed to compute Kornbrot rank difference results. The returned list is designed to be reused by higher-level functions.
rdt_data(x, ...)# S3 method for numeric
rdt_data(x, y, x_name, y_name, ...)
# S3 method for data.frame
rdt_data(x, formula, agg_fun = "error", ...)
list
(numeric)
Numeric vector or data.frame of data.
If numeric, differences of ranks correspond with x - y.
Pairs with missing values are silently dropped.
Unused additional arguments.
(numeric)
Numeric vector of data.
Differences of ranks correspond with x - y.
Pairs with missing values are silently dropped.
(Scalar character)
Name of x variable.
(Scalar character)
Name of y variable.
(formula)
A formula of form:
Use when data is in tall format.
y is the numeric outcome, group is the binary grouping variable, and block is the subject/item-level variable indicating pairs of observations.
group will be converted to a factor and the first level will be the reference value.
For example, when levels(data$group) <- c("pre", "post"), the focal level is 'post', so differences are post - pre.
Pairs with missing values are silently dropped.
See agg_fun for handling duplicate cases of grouping/blocking combinations.
Use when data is in wide format.
y and x must be numeric vectors.
Differences of ranks correspond with data$y - data$x.
Pairs with missing values are silently dropped.
(Scalar character or function: "error")
Used for aggregating duplicate cases of grouping/blocking combinations when data is in tall format and formula has structure y ~ group | block.
"error" (default) will return an error if duplicate grouping/blocking combinations are encountered.
Select one of "first", "last", "sum", "mean", "median", "min", or "max" for built in aggregation handling (each applies na.rm = TRUE).
Or define your own function.
For example, myfun <- function(x) {as.numeric(quantile(x, 0.75, na.rm = TRUE))}.