standardization_scale: pooled dispersion for a numeric variable
In optmatch: Functions for Optimal Matching

standardization_scale

R Documentation

pooled dispersion for a numeric variable

Description

Dispersion as pooled across a treatment and a control group. By default, the measure of dispersion calculated within each group is not the ordinary standard deviation as in stats::sd but rather the robust alternative encoded in stats::mad. The dispersion measurements are combined by squaring, averaging with weights proportional to one minus the sizes of the groups and then taking square roots. Used in match_on.glm.

Usage

standardization_scale(x, trtgrp, standardizer = NULL, svydesign_ = NULL)

Arguments

`x`	numeric variable
`trtgrp`	logical or numeric. If numeric, coerced to logical via `!`
`standardizer`	function, `NULL` or numeric of length 1
`svydesign_`	ordinarily `NULL`, but may also be a `survey.design2`; see Details.

Details

A non-NULL svydesign_ parameter indicates that the dispersion calculations are to be made respecting the weighting scheme implicit in that survey.design2 object. If standardizer is NULL, one gets a calculation in the style of stats::mad but with weights, performed by optmatch:::svy_sd; for a pooling of weighted standard deviations, one would pass a non-NULL svydesign_ parameter along with standardizer=optmatch:::svy_sd. (More generally, the provided standardizer function should accept as a sole argument a survey.design2 object, with nrows(svydesign_$variables) equal to the lengths of x and trtgrp. This object is expected to carry a numeric variable ‘x’, and the standardizer function is to return the dispersion of this variable.)