repeat_test: Performs repeat test across 'break_out' category.

In jlederluis/digitanalysis: Digit Analysis

Performs repeat test across break_out category.

Description

Performs repeat test across break_out category.

Usage

repeat_test(
  digitdata,
  break_out,
  data_column = NA,
  duplicate_matching_cols = "all",
  break_out_grouping = NA,
  rounding_patterns_to_omit = NA,
  plot = TRUE
)

Arguments

digitdata	A object of class DigitAnalysis.
break_out	The data column (non-numeric!) to split up the dataset based on different categories in the column if specified as an character. The first division (usually x-axis) shown in plots.
data_column	The data column to omit rounding numbers upon. Must be a single column.
duplicate_matching_cols	An array of names of data columns two rows need to match exactly in order to be defined as a repeat. Must include data_column. Default to 'all', meaning matching all columns in 'number' slot of digitdata.
break_out_grouping	A list of arrays, or defaulted to NA. Only effective if break_out is not NA. Each the names of the elements in the list is the break_out name Each array contains the values belonging to that break_out If it is remain as NA as default, while break_out is not NA, then break_out_grouping will default to every individual item in break_out will be in a separate group.
rounding_patterns_to_omit	The patterns to be counted as rounding digits to skip. Defaulted to NA. An array of characters such as c('0','00','000','5','50','500', '75', '25'). n_zeros_pattern might be helpful for generating strings of 0s.
plot	TRUE or FALSE or 'Save': If TRUE, display the plots and return them. If 'Save', return the plots but suppress display. If FALSE, no plot is produced. Default to TRUE.

Value

• A table of p values of t test for repeat test on each category

• A table of percent repeated numbers for repeat test on each category ordered by decreasing repeats percentage

• A table of sample sizes for repeat test on each category

• Plots for each category if plot = TRUE or 'Save'

• If NaN is in returned table, it means that there are no occurances of the data in that category –> 0/0 in percentage

Examples

repeat_test(digitdata)
repeat_test(digitdata, duplicate_matching_cols=c('col_name1, col_name2'))
repeat_test(digitdata, duplicate_matching_cols=c('col_name1, col_name2'), break_out='col_name')

jlederluis/digitanalysis documentation built on Nov. 5, 2023, 11:46 a.m.