Usage
outlier(data, dv, todo = "na", res.name = "outlier", upper.limit = NaN, lower.limit = NaN, limit.exact = FALSE, upper.z = NaN, lower.z = NaN, z.exact = FALSE, factors = NaN, z.keep = TRUE, z.name = "zscores", vsj = FALSE, print.summary = TRUE)
Arguments
data
A data frame containing the data to be screened as well was appropriate condition variables.
dv
Character string specifying the name of the variable within data that is to be screened for outlier. Alternatively, dv can be the appropriate column index.
todo
Character string specifying the fate of outliers: "na" - outliers are turned into NAs, "elim" - rows containing outliers are deleted from dataframe, "nothing" - nothing happens, DEFAULT: todo = "na".
res.name
Character string specifying the name of the variable wherein outliers are marked, DEFAULT: res.name = "outlier".
upper.limit
An optional numerical specifying the absolute upper limit defining outliers.
lower.limit
An optional numerical specifying the absolute lower limit defining outliers.
limit.exact
Logical, if TRUE values equal to lower.limit/upper.limit are deemed outlier.
upper.z
An optional numerical specifying how much standard deviations within a cell a value must exceed to be identified as an outlier.
lower.z
An optional numerical specifying how much standard deviations within a cell a value must undercut to be identified as an outlier.
factors
A string or vector of strings (e.g., c("subject","condition")) stating the conditions that should be used for splitting the data.
z.exact
Logical, if TRUE z-values equal to lower.z/upper.z are deemed outlier.
z.keep
Logical, if TRUE, z-scores are stored in an additional column. If FALSE, z-scores are discarded after outlier correction.
z.name
Character string, specifying a name for the variable that should be used for storing z-scores.
vsj
To be implemented in a future version...
print.summary
Logical, if TRUE, a short summary on identified outliers is printed.