Sleuth2 (version 1.0-3)

case0601: Discrimination Against the Handicapped

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

case0601

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

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