perSubjectTrim.fnc: Per-subject Trimming of Response Variable.

In LMERConvenienceFunctions: Model Selection and Post-Hoc Analysis for (G)LMER Models

Description

For each subject, removes data points that are, e.g., 2.5 standard deviations above or below the subject mean.

Usage

perSubjectTrim.fnc(data, response, subject, trim = 2.5)

Arguments

data	The data frame containing the data to be trimmed.
response	The quoted name of the column containing the to-be-trimmed data.
subject	The quoted name of the column contain subject identifiers.
trim	Threshold at which data points will be removed. Defaults to 2.5 (standard deviations above and below each subject's mean).

Value

The function returns the following objects:

data	The data with outliers removed.
data0	The original data prior to removing the outliers.
n.removed	The number of data points removed.
percent.removed	The percentage of removed data points.

Author(s)

Antoine Tremblay, Statistics Canada, [e-mail].

See Also

mcp.fnc romr.fnc

Examples

## Not run: 
if("LCFdata" %in% .packages(all.available=TRUE)){
data(eegWide)
dat<-eegWide
rm(eegWide)
gc(TRUE,TRUE)
# per subject trimming
dat <- perSubjectTrim.fnc(dat, response = "Fz", 
      subject = "Subject", trim = 2.5)$data
# ......
# n.removed = 5130 
# percent.removed = 1.584507 
}

## End(Not run)

LMERConvenienceFunctions documentation built on Oct. 23, 2020, 5:12 p.m.