imputation_list_single() objects to an imputation_list_df() object
(i.e. a list of imputation_df() objects's)Convert list of imputation_list_single() objects to an imputation_list_df() object
(i.e. a list of imputation_df() objects's)
convert_to_imputation_list_df(imputes, sample_ids)a list of imputation_list_single() objects
A list with 1 element per required imputation_df. Each element
must contain a vector of "ID"'s which correspond to the imputation_single() ID's
that are required for that dataset. The total number of ID's must by equal to the
total number of rows within all of imputes$imputations
To accommodate for method_bmlmi() the impute_data_individual() function returns
a list of imputation_list_single() objects with 1 object per each subject.
imputation_list_single() stores the subjects imputations as a matrix where the columns
of the matrix correspond to the D of method_bmlmi(). Note that all other methods
(i.e. methods_*()) are a special case of this with D = 1. The number of rows in the
matrix varies for each subject and is equal to the number of times the patient was selected
for imputation (for non-conditional mean methods this should be 1 per subject per imputed
dataset).
This function is best illustrated by an example:
imputes = list(
imputation_list_single(
id = "Tom",
imputations = matrix(
imputation_single_t_1_1, imputation_single_t_1_2,
imputation_single_t_2_1, imputation_single_t_2_2,
imputation_single_t_3_1, imputation_single_t_3_2
)
),
imputation_list_single(
id = "Tom",
imputations = matrix(
imputation_single_h_1_1, imputation_single_h_1_2,
)
)
)sample_ids <- list( c("Tom", "Harry", "Tom"), c("Tom") )
Then convert_to_imputation_df(imputes, sample_ids) would result in:
imputation_list_df(
imputation_df(
imputation_single_t_1_1,
imputation_single_h_1_1,
imputation_single_t_2_1
),
imputation_df(
imputation_single_t_1_2,
imputation_single_h_1_2,
imputation_single_t_2_2
),
imputation_df(
imputation_single_t_3_1
),
imputation_df(
imputation_single_t_3_2
)
)
Note that the different repetitions (i.e. the value set for D) are grouped together sequentially.