standardization_scale | R Documentation |

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`

.

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

`x` |
numeric variable |

`trtgrp` |
logical or numeric. If numeric, coerced to logical via |

`standardizer` |
function, |

`svydesign_` |
ordinarily |

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.)

numeric of length 1

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