.normalize_max_removed_per_cond

Normalizes max_removed_per_cond parameter for match_groups() and estimate_exhaustive().

internal

Select statistically similar research groups by backward selection using various robust algorithms, including a heuristic based on linear discriminant analysis, multiple heuristics based on the test statistic, and parallelized exhaustive search.

Kyle Gorman

ldamatch

Selection of Statistically Similar Research Groups

Géza Kiss

.normalize_max_removed_per_cond function

<dl><dt>max_removed_per_cond</dt>
<dd>A named integer vector, containing the maximum number
of subjects that can be removed from each group.
Specify 0 for groups if you want to preserve
all of their subjects. If you do not specify a value
for a group, it defaults to 2 less than the group size.
Values outside the valid range of 0..(N-1)
(where N is the number of subjects in the group)
are corrected without a warning.</dd>
<dt>condition</dt>
<dd>A factor vector containing condition labels.</dd></dl>

Arguments

Normalizes max_removed_per_cond parameter for match_groups() and estimate_exhaustive(). — .normalize_max_removed_per_cond

<dl>

<dt>max_removed_per_cond</dt>
<dd>A named integer vector, containing the maximum number
of subjects that can be removed from each group.
Specify 0 for groups if you want to preserve
all of their subjects. If you do not specify a value
for a group, it defaults to 2 less than the group size.
Values outside the valid range of 0..(N-1)
(where N is the number of subjects in the group)
are corrected without a warning.</dd>


<dt>condition</dt>
<dd>A factor vector containing condition labels.</dd>

</dl>

.normalize_max_removed_per_cond: Normalizes max_removed_per_cond parameter for match_groups() and estimate_exhaustive().

Description

Usage

Arguments