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S3 method to create a summary table of numeric variables for an exportClass object

Source: R/as_export_class.R
summaryTable.Rd

This function generates a summary table of numeric variables in an exportClass object.

Usage

summaryTable(x, ...)

# S3 method for class 'exportClass'
summaryTable(x, ..., includeFactors = FALSE, useDT = TRUE, DTstyle = TRUE)

# S3 method for class 'paradata'
summaryTable(x, ..., useDT = TRUE, DTstyle = TRUE)

Arguments

x

exportClass object.

...

further arguments.

includeFactors

if TRUE, factor variables will be converted to numeric and included in the table.

useDT

Logical, if TRUE (default) the function returns a DataTable (DT) object (HTML table), otherwise a data.table object is returned.

DTstyle

if TRUE and useDT = TRUE, then a custom style will be applied, otherwise a plain DT table will be returned.

Value

A DataTable (DT) object (HTML table) displaying the summary statistics, if useDT = TRUE, and a plain data.table otherwise.

Details

  • For the main data: The table includes statistics such as mean, standard deviation, maximum, minimum, and total count as well as count of NA values.

  • For paradata: Different summary tables for response times, duration times etc. see examples.

Examples

if (FALSE) { # suso_PwCheck() == 200
# \donttest{
questlist<-suso_getQuestDetails()

### MAIN DATA
export <- suso_export(questID = questlist$QuestionnaireId[7],
                      version = questlist$Version[7],
                      combineFiles = TRUE,
                      reloadTimeDiff = 20)

# Create a summary table
summary_data_table <- summaryTable(export)

# Display the summary table
summary_data_table
# }
}
dt <- data.table::data.table(q1 = 1:10, q2 = 11:20)
vlabs <- data.table::data.table(
  VariableName = c("q1", "q2"),
  QuestionText = c("Question 1", "Question 2")
)
ec <- exportClass(dt, varLabels = vlabs)
summaryTable(ec, useDT = FALSE)
#>    Variable      Label  Mean    SD   Max   Min Count NA_Count count
#>      <char>     <char> <num> <num> <num> <num> <num>    <num> <int>
#> 1:       q1 Question 1   5.5 3.028    10     1    NA        0    10
#> 2:       q2 Question 2  15.5 3.028    20    11    NA        0    10

if (FALSE) { # suso_PwCheck() == 200
# \donttest{
questlist<-suso_getQuestDetails()

### PARADATA
# 1. Pre-Processed tables created during export
para<-suso_export_paradata(questID = questlist$QuestionnaireId[1],
                          version = questlist$Version[1], reloadTimeDiff = 24,
                          workStatus = "All", asList = FALSE, onlyActiveEvents = TRUE)

# Create a summary table of all event counts by action (includes always passive and active one)
actions <- summaryTable(para, "action")

# Create a summary table of all event counts by user
users <- summaryTable(para, "user")

# 2. Tables created on request for response times
# grouped by variables, i.e. type, VariableName, responsible etc.

# Create a summary table of the average response time by variable
resptime_var <- summaryTable(para, "VariableName")

# Create a summary table of the average response time by question type
resptime_type <- summaryTable(para, "type")

# Create a summary table of the average response time by user
resptime_user <- summaryTable(para, "responsible")
# }
}