search_exhaustive: Searches the space backwards, prefering more subjects and...
In ldamatch: Selection of Statistically Similar Research Groups

Description Usage Arguments Details Value

Searches the space backwards, prefering more subjects and certain group size proportions.

search_exhaustive(
  condition,
  covariates,
  halting_test,
  thresh,
  props,
  max_removed_per_cond,
  tiebreaker = NULL,
  min_preserved = length(levels(condition)),
  print_info = TRUE,
  given_args = NULL,
  ...
)

`condition`	A factor vector containing condition labels.
`covariates`	A columnwise matrix containing covariates to match the conditions on.
`halting_test`	A function to apply to 'covariates' (in matrix form) which is TRUE iff the conditions are matched. Signature: halting_test(condition, covariates, thresh). The following halting tests are part of this package: `t_halt`, `U_halt`, `l_halt`, `ad_halt`, `ks_halt`, `wilks_halt`, `f_halt`. You can create the intersection of two or more halting tests using `create_halting_test`.
`thresh`	The return value of halting_test has to be greater than or equal to thresh for the matched groups.
`props`	Either the desired proportions (percentage) of the sample for each condition as a named vector, or the names of the conditions for which we prefer to preserve the subjects, in decreasing order of preference. If not specified, the (full) sample proportions are used. This is preferred among configurations with the same taken into account by the other methods to some extent. For example, c(A = 0.4, B = 0.4, C = 0.2) means that we would like the number of subjects in groups A, B, and C to be around 40%, 40%, and 20% of the total number of subjects, respectively. Whereas c("A", "B", "C") means that if possible, we would like to keep all subjects in group A, and prefer keeping subjects in B, even if it results in losing more subjects from C.
`max_removed_per_cond`	The maximum number of subjects that can be removed from each group. It must have a valid number for each group.
`tiebreaker`	NULL, or a function similar to halting_test, used to decide between cases for which halting_test yields equal values.
`min_preserved`	The minimum number of preserved subjects. It can be used to ensure that the search will not take forever to run, but instead fail when a solution is not found when preserving this number of subjects.
`print_info`	If TRUE, prints summary information on the input and the results, as well as progress information for the exhaustive search and random algorithms. Default: TRUE; can be changed using `set_param("PRINT_INFO", FALSE)`.
`given_args`	The names of arguments given to the search function.
`...`	Consumes extra parameters that are not used by the search algorithm at hand; this function gives a warning about the ones whose value is not NULL that their value is not used.

While the search is done in parallel, the search space is enormous and so it can be very slow in the worst case. It is perhaps most useful as a tool to study other matching procedures.

You can calculate the maximum possible number of cases to evaluate by calling estimate_exhaustive().

All results found by search method in a list. It raises a "Convergence failure" error if it cannot find a matched set.

ldamatch documentation built on May 23, 2021, 5:06 p.m.