des_scatterplot_matrix: Compute Pairwise Correlations

In dataquieR: Data Quality in Epidemiological Research

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	meta_data_cross

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 columns VARIABLE_LIST, cors, max_cor, min_cor

• SummaryTable: like SummaryData, 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)

dataquieR documentation built on May 29, 2024, 7:18 a.m.