report.htest-chi2.md
In report: Automated Reporting of Results and Statistical Models

report.htest-chi2 report

Code
  report(x)
Output
  Effect sizes were labelled following Funder's (2019) recommendations.

  The Pearson's Chi-squared test of independence between gender and party
  suggests that the effect is statistically significant, and small (chi2 = 30.07,
  p < .001; Adjusted Cramer's v = 0.10, 95% CI [0.07, 1.00])

Code
  report(x, rules = "funder2019")
Output
  Effect sizes were labelled following Funder's (2019) recommendations.

  The Pearson's Chi-squared test of independence between gender and party
  suggests that the effect is statistically significant, and small (chi2 = 30.07,
  p < .001; Adjusted Cramer's v = 0.10, 95% CI [0.07, 1.00])

Code
  report(x, rules = "gignac2016")
Output
  Effect sizes were labelled following Gignac's (2016) recommendations.

  The Pearson's Chi-squared test of independence between gender and party
  suggests that the effect is statistically significant, and small (chi2 = 30.07,
  p < .001; Adjusted Cramer's v = 0.10, 95% CI [0.07, 1.00])

Code
  report(x, rules = "cohen1988")
Output
  Effect sizes were labelled following Cohen's (1988) recommendations.

  The Pearson's Chi-squared test of independence between gender and party
  suggests that the effect is statistically significant, and small (chi2 = 30.07,
  p < .001; Adjusted Cramer's v = 0.10, 95% CI [0.07, 1.00])

Code
  report(x, rules = "evans1996")
Output
  Effect sizes were labelled following Evans's (1996) recommendations.

  The Pearson's Chi-squared test of independence between gender and party
  suggests that the effect is statistically significant, and very weak (chi2 =
  30.07, p < .001; Adjusted Cramer's v = 0.10, 95% CI [0.07, 1.00])

Code
  report(x, rules = "lovakov2021")
Output
  Effect sizes were labelled following Lovakov's (2021) recommendations.

  The Pearson's Chi-squared test of independence between gender and party
  suggests that the effect is statistically significant, and very small (chi2 =
  30.07, p < .001; Adjusted Cramer's v = 0.10, 95% CI [0.07, 1.00])

Code
  report(x, type = "cramers_v")
Output
  Effect sizes were labelled following Funder's (2019) recommendations.

  The Pearson's Chi-squared test of independence between gender and party
  suggests that the effect is statistically significant, and small (chi2 = 30.07,
  p < .001; Adjusted Cramer's v = 0.10, 95% CI [0.07, 1.00])

Code
  report(x, type = "pearsons_c")
Output
  Effect sizes were labelled following Funder's (2019) recommendations.

  The Pearson's Chi-squared test of independence between gender and party
  suggests that the effect is statistically significant, and small (chi2 = 30.07,
  p < .001; Pearson's c = 0.10, 95% CI [0.07, 1.00])

Code
  report(x, type = "tschuprows_t", adjust = FALSE)
Output
  Effect sizes were labelled following Funder's (2019) recommendations.

  The Pearson's Chi-squared test of independence between gender and party
  suggests that the effect is statistically significant, and very small (chi2 =
  30.07, p < .001; Tschuprow's t = 0.09, 95% CI [0.06, 1.00])

Code
  report(x, type = "tschuprows_t")
Output
  Effect sizes were labelled following Funder's (2019) recommendations.

  The Pearson's Chi-squared test of independence between gender and party
  suggests that the effect is statistically significant, and very small (chi2 =
  30.07, p < .001; Adjusted Tschuprow's t = 0.08, 95% CI [0.06, 1.00])

Code
  report(x, type = "cohens_w")
Output
  Effect sizes were labelled following Funder's (2019) recommendations.

  The Pearson's Chi-squared test of independence between gender and party
  suggests that the effect is statistically significant, and small (chi2 = 30.07,
  p < .001; Cohens_w = 0.10, 95% CI [0.07, 1.00])

Code
  report(x, type = "phi")
Output
  Effect sizes were labelled following Funder's (2019) recommendations.

  The Pearson's Chi-squared test with Yates' continuity correction of
  independence between Diagnosis and Group suggests that the effect is
  statistically significant, and large (chi2 = 31.57, p < .001; Adjusted Phi =
  0.36, 95% CI [0.25, 1.00])

Code
  report(x, type = "cohens_h", rules = "sawilowsky2009")
Output
  Effect sizes were labelled following Savilowsky's (2009) recommendations.

  The Pearson's Chi-squared test with Yates' continuity correction of
  independence between Diagnosis and Group suggests that the effect is
  statistically significant, and medium (chi2 = 31.57, p < .001; Cohen's h =
  0.74, 95% CI [0.50, 0.99])

Code
  report(x, type = "oddsratio", rules = "chen2010")
Output
  Effect sizes were labelled following Chen's (2010) recommendations.

  The Pearson's Chi-squared test with Yates' continuity correction of
  independence between Diagnosis and Group suggests that the effect is
  statistically significant, and medium (chi2 = 31.57, p < .001; Odds ratio =
  4.73, 95% CI [2.74, 8.17])

Code
  report(x, type = "riskratio")
Output


  The Pearson's Chi-squared test with Yates' continuity correction of
  independence between Diagnosis and Group suggests that the effect is
  statistically significant, and (chi2 = 31.57, p < .001; Risk_ratio = 2.54, 95%
  CI [1.80, 3.60])

Code
  report(x)
Output
  Effect sizes were labelled following Funder's (2019) recommendations.

  The Pearson's Chi-squared test of independence between mtcars$cyl and mtcars$am
  suggests that the effect is statistically significant, and very large (chi2 =
  8.74, p = 0.013; Adjusted Cramer's v = 0.46, 95% CI [0.00, 1.00])

report.htest-chi2 for given probabilities

Code
  report(x)
Output
  Effect sizes were labelled following Funder's (2019) recommendations.

  The Chi-squared test for given probabilities / goodness of fit of
  table(mtcars$cyl) to a distribution of [4: n=3.2, 6: n=9.6, 8: n=19.2] suggests
  that the effect is statistically significant, and medium (chi2 = 21.12, p <
  .001; Fei = 0.27, 95% CI [0.17, 1.00])