Correlation Heatmap module
mod_corr_hm.Rd
Display a heatmap of correlation coefficients (Pearson, Spearman) along with confidence intervals and p-values between dataset parameters over a single visit.
Usage
corr_hm_UI(
id,
default_cat = NULL,
default_par = NULL,
default_visit = NULL,
default_corr_method = NULL
)
corr_hm_server(
id,
bm_dataset,
subjid_var = "SUBJID",
cat_var = "PARCAT",
par_var = "PARAM",
visit_var = "AVISIT",
value_vars = c("AVAL", "PCHG"),
default_value = NULL
)
mod_corr_hm(
module_id,
bm_dataset_name,
subjid_var = "SUBJID",
cat_var = "PARCAT",
par_var = "PARAM",
visit_var = "AVISIT",
value_vars = c("AVAL", "PCHG"),
default_cat = NULL,
default_par = NULL,
default_visit = NULL,
default_value = NULL,
bm_dataset_disp
)
Arguments
- id
[character(1)]
Shiny ID
- default_cat
Default selected categories
- default_par
Default selected parameters
- default_visit
Default selected visits
- default_corr_method
Name of default correlation method
- bm_dataset
[data.frame()]
An ADBM-like dataset similar in structure to the one in this example, with one record per subject per parameter per analysis visit.
It should have, at least, the columns specified by the parameters
subjid_var
,cat_var
,par_var
,visit_var
andvalue_vars
. The semantics of these columns are as described in the CDISC standard for variables USUBJID, PARCAT, PARAM, AVISIT and AVAL, respectively.- subjid_var
[character(1)]
Column corresponding to the subject ID
- cat_var, par_var, visit_var
[character(1)]
Columns from
bm_dataset
that correspond to the parameter category, parameter and visit- value_vars
[character(n)]
Columns from
bm_dataset
that correspond to values of the parameters- default_value
[character(1)|NULL]
Default values for the selectors
- module_id
Shiny ID
[character(1)]
Module identifier
- bm_dataset_name
[character(1)]
Biomarker dataset name
- bm_dataset_disp
[mm_dispatcher(1)]
module manager dispatchers passed asbm_dataset
andgroup_dataset
tocorr_hm_server