test_pdiff {esci}

Test a hypothesis about a difference in proportion

Description

test_pdiff is suitable for testing a hypothesis about a difference in proportions between two conditions with a categorical outcome variable. It can test hypotheses for both independent and paired designs.

Usage

test_pdiff(estimate, rope = c(0, 0), output_html = FALSE)

Arguments

estimate

• An esci_estimate object generated by an estimate_pdiff_ function

rope

• A two-element vector defining the Region of Practical Equivalence (ROPE). Specify c(0, 0) to test a point null of exactly 0. Specify any two ascending values between -1 and 1 to test an interval null (e.g. c(-.25, .25) to test the hypothesis that the difference in proportion is between -.25 and .25).

output_html

• TRUE to return results in HTML; FALSE (default) to return standard output

Details

This function can be passed an esci_estimate object generated by estimate_pdiff_one(), estimate_pdiff_two(), estimate_pdiff_paired(), or estimate_pdiff_ind_contrast().

It can test hypotheses about a specific value for the difference (a point null) or about a range of values (an interval null)

Value

Returns a list with 1-2 data frames

• point_null - always returned

  • test_type - 'Nil hypothesis test', meaning a test against H0 = 0

  • outcome_variable_name - Name of the outcome variable

  • effect - Label for the effect being tested

  • null_words - Express the null in words

  • confidence - Confidence level, integer (95 for 95%, etc.)

  • LL - Lower boundary of the confidence% CI for the effect

  • UL - Upper boundary of the confidence% CI for the effect

  • CI - Character representation of the CI for the effect

  • CI_compare - Text description of relation between CI and null

  • t - If applicable, t value for hypothesis test

  • df - If applicable, degrees of freedom for hypothesis test

  • p - If applicable, p value for hypothesis test

  • p_result - Text representation of p value obtained

  • null_decision - Text represention of the decision for the null

  • conclusion - Text representation of conclusion to draw

  • significant - TRUE/FALSE if significant at alpha = 1-CI

• interval_null - returned only if an interval null is specified

  • test_type - 'Practical significance test', meaning a test against an interval null

  • outcome_variable_name -

  • effect - Name of the outcome variable

  • rope - Test representation of null interval

  • confidence - Confidence level, integer (95 for 95%, etc.)

  • CI - Character representation of the CI for the effect

  • rope_compare - Text description of relation between CI and null interval

  • p_result - Text representation of p value obtained

  • conclusion - Text representation of conclusion to draw

  • significant - TRUE/FALSE if significant at alpha = 1-CI

Examples

estimate <- estimate_pdiff_two(
  comparison_cases = 10,
  comparison_n = 20,
  reference_cases = 78,
  reference_n = 252,
  grouping_variable_levels = c("Original", "Replication"),
  conf_level = 0.95
)

# Test against null of exactly
test_pdiff(estimate)

# Test against null of (-0.1, 0.1)
test_pdiff(estimate, rope = c(-0.1, 0.1))