Discrimination Against the Handicapped
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.
case0601
A data frame with 70 observations on the following 2 variables.
Scoreis the score each student gave to the applicant
Handicapis a factor variable with 5
levels—"None", "Amputee", "Crutches",
"Hearing" and "Wheelchair"
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.
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.
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
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