match_numeric | R Documentation |
Randomly select test groups/individuals and create matching control groups/individuals by using Euclidean distance on scaled numeric variables. The data frame must contain the group/individual labels in the first column and the other variables must be in levels, in other words not scaled.
match_numeric(df, n = 10, test_list = NULL)
df |
data frame of numeric inputs. First column must have group/individuals names, 1 line per group/individuals. |
n |
size of the test group, and matching control group. Defaults to 10. Defaults to 10. Will be ignored if df provide to the "test_list" parameter. |
test_list |
df with one column named "TEST." This has a list of members in the current test. Defaults to NULL. |
In the case where duplicates arise in the Control, the function iterates through the test control list until there are no duplicates in the Control. In each iteration, it re-ranks the remaining possible control groups/individuals and matches to the test on the lowest distance.
You can supply a data frame of pre-selected test groups/individuals to the parameter test_list and the function will provide you with a list of control groups/individuals.
If the "n" parameter is used, the function outputs a data frame with a list of randomized test groups/individuals from the supplied df with matching control groups/individuals, a 1 to 1 match. If a data frame is supplied to the "test_list" parameter, 1 to 1 matching control stores will be created for the groups/individuals in the "TEST" column supplied to the "test_list" parameter.
library(dplyr) library(magrittr) df <- datasets::USArrests %>% dplyr::mutate(state = base::row.names(datasets::USArrests)) %>% dplyr::select(state, dplyr::everything()) TEST_CONTROL_LIST <- TestContR::match_numeric(df, n = 15)
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