View source: R/impute_artifacts.R
impute_artifacts | R Documentation |
Impute missing and impossible artifact values
impute_artifacts(
sample_id = NULL,
construct_id = NULL,
measure_id = NULL,
art_vec,
cat_moderator_matrix,
impute_method = "bootstrap_mod",
art_type = "rel",
n_vec = rep(1, length(art_vec))
)
sample_id |
Study ID value. |
construct_id |
Construct name or other designator. |
measure_id |
Measure name or other designator. |
art_vec |
Vector of artifact values |
cat_moderator_matrix |
Matrix of categorical moderators |
impute_method |
Method to use for imputing artifacts. Choices are:
|
art_type |
Type of artifacts to be imputed: "rel" for reliabilities and "u" for u ratios. |
n_vec |
Vector of sample sizes associated with the elements of art_vec. |
A vector of artifacts that includes imputed values.
# art_vec <- c(.6, .7, NA, .8, .9, NA)
# cat_moderator_matrix <- matrix(c(rep(1, 3), rep(2, 3)))
# art_type <- "rel"
# n_vec <- c(50, 200, 100, 50, 200, 100)
#
# ## Compute unweighted means
# impute_artifacts(art_vec = art_vec, cat_moderator_matrix = cat_moderator_matrix,
# impute_method = "unwt_mean_full", art_type = art_type, n_vec = n_vec)
# impute_artifacts(art_vec = art_vec, cat_moderator_matrix = cat_moderator_matrix,
# impute_method = "unwt_mean_mod", art_type = art_type, n_vec = n_vec)
#
# ## Compute weighted means
# impute_artifacts(art_vec = art_vec, cat_moderator_matrix = cat_moderator_matrix,
# impute_method = "wt_mean_full", art_type = art_type, n_vec = n_vec)
# impute_artifacts(art_vec = art_vec, cat_moderator_matrix = cat_moderator_matrix,
# impute_method = "wt_mean_mod", art_type = art_type, n_vec = n_vec)
#
# ## Simulate from distribution with the mean and variance of the observed artifacts
# impute_artifacts(art_vec = art_vec, cat_moderator_matrix = cat_moderator_matrix,
# impute_method = "simulate_full", art_type = art_type, n_vec = n_vec)
# impute_artifacts(art_vec = art_vec, cat_moderator_matrix = cat_moderator_matrix,
# impute_method = "simulate_mod", art_type = art_type, n_vec = n_vec)
#
# ## Sample random values from the observed distribution of artifacts
# impute_artifacts(art_vec = art_vec, cat_moderator_matrix = cat_moderator_matrix,
# impute_method = "bootstrap_mod", art_type = art_type, n_vec = n_vec)
# impute_artifacts(art_vec = art_vec, cat_moderator_matrix = cat_moderator_matrix,
# impute_method = "bootstrap_full", art_type = art_type, n_vec = n_vec)
#
# ## If all values are missing from a moderator category, the program will run
# ## full-data imputation on the remaining missing values:
# impute_artifacts(art_vec = c(NA, NA, NA, .7, .8, .9), cat_moderator_matrix = cat_moderator_matrix,
# impute_method = "bootstrap_mod", art_type = art_type, n_vec = n_vec)
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