cem (version 1.0.96)

L1.meas: Evaluates L1 distance between multidimensional histograms

Description

Evaluates L1 distance between multidimensional histograms

Usage

L1.meas(group, data, drop=NULL, breaks = NULL, weights)

Arguments

group

the group variable

data

the data

drop

a vector of variable names in the data frame to ignore

breaks

a list of vectors of cutpoints; if not specified, automatic choice will be made

weights

weights

Value

• An object of class L1.meas which is a list with the following fields
• L1
  The numerical value of the L1 measure
• breaks
  A list of cutpoints used to calculate the L1 measure
• LCS
  The numerical value of the Local Common Support proportion

Details

This function calculates the L1 distance on the k-dimensional histogram.

If breaks is not specified, the Scott automated bin calculation is used (which coarsens less than Sturges, which used in cem). Please refer to cem help page. In this case, breaks are used to calculate the L1 measure.

If breaks is missing, the default rule to calculate cutpoints is the Scott's rule.

This code also calculate the Local Common Support (LCS) measure, which is the proportion of non empty k-dimensional cells of the histogram which contain at least one observation per group.

References

Stefano Iacus, Gary King, Giuseppe Porro, ``Matching for Casual Inference Without Balance Checking,'' http://gking.harvard.edu/files/abs/cem-abs.shtml

Examples

data(LL)
L1.meas(LL$treated,LL, drop=c("treated","re78"))