sampcompR (version 0.3.0)

biv_bias_per_variable: Returns a table based on the information of a biv_compare_object that indicates the Average Absolute Bias (AARB) in Pearson's r or the Average Absolute Relative Bias (AARB) in Pearson's r for every data frame It can be outputted as HTML or LaTex Table, for example with the help of the stargazer function.

Description

Returns a table based on the information of a biv_compare_object that indicates the Average Absolute Bias (AARB) in Pearson's r or the Average Absolute Relative Bias (AARB) in Pearson's r for every data frame It can be outputted as HTML or LaTex Table, for example with the help of the stargazer function.

Usage

biv_bias_per_variable(
  biv_compare_object,
  type = "rel_diff",
  final_col = "difference",
  ndigits = 3,
  varlabels = NULL,
  label_df = NULL
)

Value

A matrix, that shows the Average Absolute Bias (AAB) or the Average Absolute Relative Bias (AARB) for every individual variable. This is given separately for every comparison data frame, as well as averaged over comparisons, or as the difference between the first and the last comparison.

Arguments

biv_compare_object

A object returned by the biv_compare function.

type

A character string, which is "AAB" if the Average Absolute Bias per variable should be displayed in the table, or "AARB" if the Average Absolute Relative Bias per Variable should be displayed in the table.

final_col

A character string, indicating if the last column of the table should display an average bias per variable of over all data frames ("average"), or the difference between the first and the average bias of the first and the last data frame ("difference").

ndigits

Number of digits that is shown in the table.

varlabels

A character vector containing labels for the variables.

label_df

A character vector containing labels for the data frames.

Examples

data("card")

north <- card[card$south==0,]
white <- card[card$black==0,]

## use the function to plot the data 
bivar_data<-sampcompR::biv_compare(dfs = c("north","white"),
                                   benchmarks = c("card","card"),
                                   variables= c("age","educ","fatheduc","motheduc","wage","IQ"),
                                   data=TRUE)

table1<-sampcompR::biv_bias_per_variable(bivar_data,type="rel_diff",
                                         final_col="average",ndigits=2)
noquote(table1)

table2<-sampcompR::biv_bias_per_variable(bivar_data,type = "diff",
                                         final_col="difference",ndigits=2)
noquote(table2)