esci (version 1.0.7)

test_correlation: Test a hypothesis about the strength of a Pearson's r correlation

Description

test_correlation is suitable for testing a hypothesis about a the strength of correlation between two continuous variables (designs in which Pearson's r is a suitable measure of correlation).

Usage

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

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

Arguments

estimate

• An esci_estimate object generated by the estimate_r 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, .45) to test the hypothesis that Pearson's r in the population (rho) is between .25 and .45).

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_r().

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

Examples

# example code
estimate <- esci::estimate_r(r = 0.536, n = 50)

# Test against a point null of exactly 0
test_correlation(estimate)

# Test against an interval null (-0.1, 0.1)
test_correlation(estimate, rope = c(-0.1, 0.1))