case0601: Discrimination Against the Handicapped

Description Usage Format Source References Examples

Description

Study explores how physical handicaps affect people's perception of employment qualifications. Researchers prepared 5 videotaped job interviews using actors with a script designed to reflect an interview with an applicant of average qualifications. The 5 tapes differed only in that the applicant appeared with a different handicap in each one. Seventy undergraduate students were randomly assigned to view the tapes and rate the qualification of the applicant on a 0-10 point scale.

Usage

1

Format

A data frame with 70 observations on the following 2 variables.

Score

is the score each student gave to the applicant

Handicap

is a factor variable with 5 levels—"None", "Amputee", "Crutches", "Hearing" and "Wheelchair"

Source

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

References

Cesare, S.J., Tannenbaum, R.J. and Dalessio, A. (1990). Interviewers' Decisions Related to Applicant Handicap Type and Rater Empathy, Human Performance 3(3): 157–171.

Examples

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str(case0601)
boxplot(Score~Handicap, data=case0601, ylab="Score")
aov.handicap <- aov(Score ~ Handicap, case0601)
summary(aov.handicap)
TukeyHSD(aov.handicap)

#Calculate confidence interval for linear combination
#(wheelchair+crutches)/2 - (amputee+hearing)/2 as in Display 6.4
mean.handicaps <- with(case0601, tapply(Score, Handicap, mean))
var.handicaps <- with(case0601, tapply(Score, Handicap, var))

n <- 14
s.pooled <- sqrt(sum((n-1)*var.handicaps)/sum((n-1)*5))

## either
cr.wh <- mean.handicaps["Wheelchair"] + mean.handicaps["Crutches"]
am.he <- mean.handicaps["Amputee"] + mean.handicaps["Hearing"]
g <- cr.wh/2 - am.he/2
## or
contr <- c(0, -1, 1, -1, 1)/2
g <- sum(contr * mean.handicaps)

se.g <- s.pooled * sqrt(sum(contr^2)/n)
t.65 <- qt(.975, 65)
## ci
g + c(-1,1) * t.65 * se.g

Sleuth2 documentation built on Jan. 24, 2019, 9:04 a.m.