| stat_tcs {callback} | R Documentation |
Total callback shares
Description
Computes the callback shares and their confidence intervals. The analysis is restricted to the tests with at least one callback. It is the definition used in Riach and Rich (2006).
Usage
stat_tcs(x, level = 0.95)
Arguments
x |
a |
level |
a number, containing the level of the confidence intervals (0.95 by default). |
Value
A list with class "stat_tcs" containing 8 components : level, props,
cp, wilson, student, t.student, t.pearson and t.fisher.
level: the level of the confidence intervals.
props: a data frame containing the following variables.
ncall: number of callbacks.
c10: number of tests with the 1st candidate preferred (2nd candidate discriminated against).
c01: number of tests with the 2nd candidate preferred (1st candidate discriminated against).
c11: number of tests with both candidates called back.
p_cand1: 1st candidate total callback share (c10/ncall).
p_cand2: 2nd candidate total callback share (c01/ncall).
p_equal: equal treatment callback share (c11/ncall).
p_cand_dif: p_cand1-p_cand2.
cp: a data frame containing the Clopper-Pearson confidence intervals,
from binom.test(), and the p-value of the Fisher test of independence between
the candidate type and the callback variable, from fisher.test().
inf_p_cand1: 1st candidate total callback share, lower bound.
sup_p_cand1: 1st candidate total callback share, upper bound.
inf_p_cand2: 2nd candidate total callback share, lower bound.
sup_p_cand2: 2nd candidate total callback share, upper bound.
inf_p_equal: equal treatment total callback rate, lower bound.
sup_p_equal: equal treatment total callback rate, upper bound.
wilson: a data frame containing the Wilson confidence intervals
and the p-value of the equality test of callback shares between the two
candidates, from prop.test().
inf_p_cand1: 1st candidate total callback share, lower bound.
sup_p_cand1: 1st candidate total callback share, upper bound.
inf_p_cand2: 2nd candidate total callback share, lower bound.
sup_p_cand2: 2nd candidate total callback share, upper bound.
inf_p_equal: equal treatment total callback rate, lower bound.
sup_p_equal: equal treatment total callback rate, upper bound.
inf_cand_dif: p_c10-p_c01, lower bound.
sup_cand_dif: p_c10-p_c01, upper bound.
student: a data frame containing the Student confidence intervals
and the p-value of the equality test of callback shares between the two
candidates.
inf_p_cand1: 1st candidate total callback share, lower bound.
sup_p_cand1: 1st candidate total callback share, upper bound.
inf_p_cand2: 2nd candidate total callback share, lower bound.
sup_p_cand2: 2nd candidate total callback share, upper bound.
inf_p_equal: equal treatment total callback rate, lower bound.
sup_p_equal: equal treatment total callback rate, upper bound.
inf_cand_dif: p_c10-p_c01, lower bound.
sup_cand_dif: p_c10-p_c01, upper bound.
t.fisher: a data frame containing the statistics of the Fisher test.
p_cand_dif: p_cand1-p_cand2.
p_Fisher: the p-value of the Fisher test.
s_Fisher: the significance code of the Fisher test.
t.pearson: a data frame containing the statistics of the Pearson test.
p_cand_dif: p_cand1-p_cand2.
Pearson: the value of Pearson's chi-squared test statistic.
p_Pearson: the p-value of the Pearson test.
s_Pearson: the significance code of the Pearson test.
t.student: A data frame containing the statistics of the Student test.
p_cand_dif: p_cand1-p_cand2.
Student: the value of Student's test statistic.
p_Student: the p-value of the Student test.
s_Student: the significance code of the Student test.
Author(s)
Emmanuel Duguet
References
Clopper, C. J. & Pearson, E. S. (1934). The use of confidence or fiducial limits illustrated in the case of the binomial. Biometrika, 26, 404–413. doi:10.2307/2331986.
Riach, P. A., & Rich, J. (2006). An experimental investigation of sexual discrimination in hiring in the English labor market. The BE Journal of Economic Analysis & Policy, 6(2),
Wilson, E.B. (1927). Probable inference, the law of succession, and statistical inference. Journal of the American Statistical Association, 22, 209–212. doi:10.2307/2276774.
Examples
data(labour1)
x <- callback(data=labour1,cluster="offer",candid="hist",callback="callback")
str(stat_ecs(x,level=0.9))