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Significance testing

Source: R/stat_test_y2.R
sig_test_y2.Rd

Akin to crosstabs, run significance testing on a grouped frequencies

Usage

sig_test_y2(
  frequencies,
  dataset,
  banner_var,
  wt = NULL,
  layout = c("tall", "wide")
)

Arguments

frequencies

A grouped frequencies table created using the freqs() function in y2clerk

dataset

The original data frame that the frequencies table came from

banner_var

This will be the banner variables for cross tabs. Must be the same as the grouping variable from the freqs() function.

wt

The weight variable used in the frequencies function, if applicable

layout

(default: 'tall') 'tall' formats the output to look like a basic grouped freqs table. 'wide' formats the output to look like the result from Q-formatted cross tabs

Value

A table that matches the output of cross tabs, showing significance differences between different groups for any input variables stats, cross tabs. Column comparison symbols: a, b, c... (p <= 0.05), A, B, C... (p <= 0.001); No symbol: not significant at at least (p <= 0.05)

Examples


# Example Data

df <- data.frame(
  V1 = c(
    rep('Agree', 100),
    rep('Neither', 100),
    rep('Disagree', 100),
    rep('Agree', 200),
    rep('Neither', 50),
    rep('Disagree', 50),
    rep('Agree', 50),
    rep('Neither', 125),
    rep('Disagree', 125)
  ),
  group = c(
    rep('Group 1', 300),
    rep('Group 2', 300),
    rep('Group 3', 300)
  ),
  weight = c(
    rnorm(900, 1, 0.25)
  )
)

# Frequencies

frequencies <- df |>
  dplyr::group_by(group) |>
  freqs(V1)
#> Adding missing grouping variables: `group`

# Frequencies with significance tests

tested_freqs <- frequencies |>
  sig_test_y2(dataset = df,
              banner_var = group)
#> Adding grouped pairwise significance tests for response "Agree" for group_var "group"
#> Adding grouped pairwise significance tests for response "Disagree" for group_var "group"
#> Adding grouped pairwise significance tests for response "Neither" for group_var "group"

# Tested frequencies in crosstab format

tested_freqs <- frequencies |>
  sig_test_y2(dataset = df,
              banner_var = group,
              layout = 'wide')
#> Adding grouped pairwise significance tests for response "Agree" for group_var "group"
#> Adding grouped pairwise significance tests for response "Disagree" for group_var "group"
#> Adding grouped pairwise significance tests for response "Neither" for group_var "group"

# Weighted tested frequencies

tested_freqs <- df |>
  dplyr::group_by(group) |>
  freqs(V1,
        wt = weight) |>
  sig_test_y2(dataset = df,
              banner_var = group,
              wt = weight)
#> Adding missing grouping variables: `group`
#> Adding grouped pairwise significance tests for response "Agree" for group_var "group"
#> Adding grouped pairwise significance tests for response "Disagree" for group_var "group"
#> Adding grouped pairwise significance tests for response "Neither" for group_var "group"

# Weighted tested frequencies in crosstab format

tested_freqs <- df |>
  dplyr::group_by(group) |>
  freqs(V1,
        wt = weight) |>
  sig_test_y2(dataset = df,
              banner_var = group,
              wt = weight,
              layout = 'wide')
#> Adding missing grouping variables: `group`
#> Adding grouped pairwise significance tests for response "Agree" for group_var "group"
#> Adding grouped pairwise significance tests for response "Disagree" for group_var "group"
#> Adding grouped pairwise significance tests for response "Neither" for group_var "group"