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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/employee.R
\docType{data}
\name{employee}
\alias{employee}
\title{Employee selection data}
\format{
A data frame with 20 rows and 3 variables:
\describe{
\item{IQ}{candidate IQ score}
\item{wbeing}{candidate well-being score}
\item{jobperf}{candidate job performance score}
}
}
\source{
Enders (2010), Applied Missing Data Analysis, p. 218
}
\usage{
employee
}
\description{
A toy example from Craig Enders.
}
\details{
Enders describes these data as follows:
I designed these data to mimic an employee selection scenario in
which prospective employees complete an IQ test and a
psychological well-being questionnaire during their interview.
The company subsequently hires the applications that score in the
upper half of the IQ distribution, and a supervisor rates their
job performance following a 6-month probationary period.
Note that the job performance scores are missing at random (MAR)
(i.e. individuals in the lower half of the IQ distribution were
never hired, and thus have no performance rating). In addition,
I randomly deleted three of the well-being scores in order to
mimic a situation where the applicant's well-being questionnaire
is inadvertently lost.
A larger version of this data set in present as
\code{\link[miceadds:data.enders]{data.enders.employee}}.
}
\keyword{datasets}
|
