single_high_low_test: Perform a single high low test. Helper function for...
In jlederluis/digitanalysis: Digit Analysis

single_high_low_test

R Documentation

Perform a single high low test. Helper function for `high_low_test`.

Description

Perform a single high low test. Helper function for high_low_test.

Usage

single_high_low_test(
  digitdata,
  contingency_table,
  data_columns,
  high,
  omit_05,
  skip_first_digit,
  skip_last_digit,
  category,
  category_grouping,
  test_type
)

Arguments

`digitdata`	A object of class `DigitAnalysis`.
`contingency_table`	The user-input probability table of arbitrary distribution. Overwrites `distribution` if not NA. Must be a dataframe of the form as `benford_table`. Defaulted to NA. Check out `load(file = "data/benford_table.RData")` to see the format of `benford_table`
`data_columns`	The names of numeric columns of data to be analyzed. Default can be 'all', where using all data columns in `numbers` df in `digitdata`; an array of column names, as characters; a single column name, as character.
`high`	An numeric array of digits or a single number that will be classified as high digits. Defaulted to c(6,7,8,9).
`omit_05`	Whether to omit 0 or both 0 and 5. If omit both 0 and 5, pass in c(0,5) or c(5,0); if omit only 0 pass in 0 or c(0); if omit neither, pass in NA. Default to NA.
`skip_first_digit`	TRUE or FALSE: If TRUE, skip first digit place before analysis. Default to FALSE.
`skip_last_digit`	TRUE or FALSE: If TRUE, skip last digit place before analysis, since we don't want tests to overlap. Default to FALSE. `skip_last_digit` should overwrite `digit_places` and `skip_first_digits`.
`category`	The column for splitting the data into sectors for separate analysis. The second division (usually variables) shown in plots.
`category_grouping`	A list of arrays, or defaulted to NA. Only effective if `category` is not NA. Each the names of the elements in the list is the category name Each array contains the values belonging to that category If it is remain as NA as default, while `category` is not NA, then `category_grouping` will default to every individual item in `category` will be in a separate group. e.g. `category_grouping = list(group_1=c(category_1, category_2, ...), group_2=c(category_10, ...), group_3=c(...))`
`test_type`	Specifies whether to perform a binomial test on high vs low digit frequency weighted averaged across digit places with "binom", or a chi square test on high vs. low by each digit place with "chisq". Defaulted to "chisq".