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include correlation pair validation

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Andreas Gammelgaard Damsbo 2025-09-23 09:22:46 +02:00
parent 136480ca3d
commit b45a4d9003
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1 changed files with 45 additions and 2 deletions
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47
R/validation.R
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@ -215,6 +215,19 @@ missings_validate <- function(data){
} }
} }
corr_pairs_validate <- function(data){
data_s <- if (shiny::is.reactive(data)) data() else data
if (!0 %in% dim(data_s)) {
# browser()
n_pairs <- nrow(data_s)
data.frame(
n_pairs = n_pairs
)
} else {
data.frame(NULL)
}
}
######################################################################## ########################################################################
############# Collected validation functions in a library-like function ############# Collected validation functions in a library-like function
@ -264,10 +277,10 @@ validation_lib <- function(name=NULL) {
test.fun.args = list(var = "p_out", cut = 50) test.fun.args = list(var = "p_out", cut = 50)
) )
}, },
"missings" = function(x, y) { "missings" = function(x) {
### Placeholder for missingness validation ### Placeholder for missingness validation
list( list(
string = "There are {p_miss} % missing observations.", string = i18n$t("There are {p_miss} % missing observations."),
summary.fun = missings_validate, summary.fun = missings_validate,
summary.fun.args = list( summary.fun.args = list(
data = x data = x
@ -278,6 +291,36 @@ validation_lib <- function(name=NULL) {
}, },
test.fun.args = list(var = "p_miss", cut = 30) test.fun.args = list(var = "p_miss", cut = 30)
) )
},
# "mcar" = function(x) {
# ### Placeholder for missingness validation
# list(
# string = i18n$t("There are {p_miss} % missing observations."),
# summary.fun = missings_validate,
# summary.fun.args = list(
# data = x
# ),
# test.fun = function(x, var, cut) {
# test.var <- x[var]
# ifelse(test.var > cut, "warning", "succes")
# },
# test.fun.args = list(var = "p_miss", cut = 30)
# )
# },
"corr_pairs" = function(x) {
### Placeholder for missingness validation
list(
string = i18n$t("Data includes {n_pairs} pairs of highly correlated variables."),
summary.fun = corr_pairs_validate,
summary.fun.args = list(
data = x
),
test.fun = function(x, var, cut) {
test.var <- x[var]
ifelse(test.var > cut, "warning", "succes")
},
test.fun.args = list(var = "n_pairs", cut = 0)
)
} }
) )