Computes Statistics from Discrimination Experimental Data


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Documentation for package ‘callback’ version 0.1.3

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address1 Origin/Gender discrimination and strongly negative mediatic exposure (information technologist)
callback Data formatting
callback_comp Creates the estimation data for a component model
gender1 Gender/Maternity discrimination (commercial and administrative jobs in the financial sector)
gender2 Gender/Maternity discrimination (electricians)
gender3 Gender/Maternity discrimination (masons)
gender4 Gender/Maternity discrimination (plumbers)
g_difp Difference of proportions plot
g_ecs Exclusive callback shares plot
g_mcr Proportions' comparison plot
g_raw Raw callback rates plot
g_tcs Total callback shares plot
inter1 Gender/Origin discrimination (software developer)
is.calc Computational compatibility
labour1 Labour market history discrimination (accountants)
labour2 Labour market history discrimination (sales assistant)
mobility1 Gender discrimination and mobility (management controller)
origin1 Origin discrimination (accountants)
origin2 Origin discrimination (waiters)
plot.callback_stat Plots for callback rates and shares
print.callback Prints the structure of the experiment
print.callback_comp Prints the structure of a component model
print.callback_reg Prints the components of a component model
print.callback_stat Prints the callback proportions analysis
print.stat_paired Print the callback counts analysis
reg Generic regression function
reg.callback_comp Component model estimation
reg_als Asymptotic least squares estimation
stat_colsums Sums the numeric or logical columns in a data frame.
stat_ecs Exclusive callback shares
stat_mcr Matched callback rates
stat_paired Callback counts on paired data
stat_raw Unmatched callback rates
stat_signif Significance code of a p-value
stat_tcs Total callback shares
summary.callback_reg Prints the regression table of a component model
train1 Training profile impact (plumbers)
train2 Training profile impact (waiters)