| des_scatterplot_matrix {dataquieR} | R Documentation |
Compute Pairwise Correlations
Description
works on variable groups (cross-item_level), which are expected to show
a Pearson correlation
Usage
des_scatterplot_matrix(
study_data,
meta_data,
label_col = LABEL,
meta_data_cross_item = "cross-item_level"
)
Arguments
study_data |
data.frame the data frame that contains the measurements |
meta_data |
data.frame the data frame that contains metadata attributes of study data |
label_col |
variable attribute the name of the column in the metadata with labels of variables |
meta_data_cross_item |
Details
Descriptor # TODO: This can be an indicator
Value
a list with the slots:
-
SummaryPlotList: for each variable group a ggplot object with pairwise correlation plots -
SummaryData: table with columnsVARIABLE_LIST,cors,max_cor,min_cor -
SummaryTable: likeSummaryData, but machine readable and with stable column names.
Examples
## Not run:
devtools::load_all()
prep_load_workbook_like_file("meta_data_v2")
des_scatterplot_matrix("study_data")
## End(Not run)
[Package dataquieR version 2.1.0 Index]