Changes in version 1.9.0 (2026-01-12) Changes: - New functions: - size.ci.sd -- Computes sample size for a traditional standard deviation confidence interval - size.ci.cronbach.prior -- Computes sample size for a Cronbach reliablity confidence interval using a planning value from a prior study - size.ci.icc.prior -- Computes sample size for an intraclass correlation confidence interval using a planning value from a prior study - size.ci.icc -- Computes sample size for an intraclass correlation confidence interval - ci.diversity -- Computes estimates and confidence intervals for three types of diversity indices - ci.mean.gen -- Computes confidence intervals for three types of generalized means - ci.sd -- Computes the traditional confidence interval for a population standard deviation - ci.lc.prop.scheffe -- Computes a Scheffe confidence interval and p-value for a linear contrast of population proportions - ci.lc.mean.scheffe -- Computes a Scheffe confidence interval and p-value for a linear contrast of population means - ci.icc -- Computes intraclass reliability coefficients using mean square estimates as input - ci.slope -- Computes confidence interval for slope in a simple linear model using summary statistics as input - pi.cronbach -- Computes a prediction interval for a Cronbach reliability in a future sample - References Manual - Most function descriptions now refer to a specific section in the Bonett (2021) online text for additional details - Error Corrections: - size.ci.prop.prior -- corrected a error in the sample size computation Changes in version 1.8.0 (2025-06-10) Changes: - New functions: - test.mono.median.bs -- Hypothesis test of a monotonic trend in medians for an ordered between-subjects factor - ci.slope.median.bs -- Computes confidence interval for the slope of medians in a one-factor experimental design with a quantitative between-subjects factor - size.ci.cv -- Computes sample size for a coefficient of variation confidence interval in a 1-group design - size.ci.median -- Computes sample size for a median confidence interval in a 1-group design - size.ci.median2 -- Computes sample size for a median difference confidence interval in a 2-group design - size.ci.lc.median.bs -- Computes sample size for a linear contrast of medians confidence interval in a between-subjects design - size.ci.gen -- Computes sample size for a confidence interval for any type of parameter in a 1-group design - size.ci.gen2 -- Computes sample size for a confidence interval for the difference in any type of parameter in a 2-group design - size.test.gen -- Computes sample size for a test of any type of parameter in a 1-group design - size.test.gen2 -- Computes sample size for a test of the difference of any type of parameter in a 2-group design - Modifications: - ci.prop now adds an exact confidence interval - Deleted functions: - ci.mean1 has been replaced with ci.mean - ci.prop1 has been replaced with ci.prop - ci.median1 has been replaced with ci.median - ci.stdmean1 has been replaced with ci.stdmean - pi.var.upper has been replaced with pi.var Changes in version 1.7.0 (2024-12-18) Changes: - New functions: - size.ci.oddsratio -- Computes sample size for an odds ratio confidence interval - size.ci.yule -- Computes sample size for a Yule's Q confidence interval - size.ci.phi -- Computes sample size for a phi correlation confidence interval - size.ci.biphi -- Computes sample size for a biserial-phi correlation confidence interval - size.ci.ancova2 -- Computes sample size for a 2-group ANCOVA confidence interval - size.ci.slope.gen -- Computes sample size for a slope coefficient confidence interval in a general model - size.test.ancova2 -- Computes sample size for a 2-group ANCOVA hypothesis test - size.test.slope.gen -- Computes sample size for a slope coefficient hypothesis test in a general model - signal -- Computes parameter estimates in a Yes/No signal detection study - exp.slope -- Computes confidence intervals for exp(B) and 100(exp(B) - 1)% - ci.bayes.cor -- Computes Bayesian credible interval for a Pearson or partial correlation with a skeptical prior - ci.bayes.spcor -- Computes Bayesian credible interval for a semipartial correlation with a skeptical prior - pi.var -- Computes one-sided or two-sided prediction limits for an estimated variance in a future study (will replace pi.var.upper) - Modifications - size.ci.prop2 can now solve for equal or unequal sample sizes. Requires a new argumnet, R, specifying the ratio of sample sizes and now returns a 2-column matrix. - size.ci.ratio.prop2 can now solve for equal or unequal sample sizes. Requires a new argument, R, specifying the ratio of sample sizes and now returns a 2-column matrix. - size.test.cor2 can now solve for equal or unequal sample sizes. Requires a new argument, R, specifying the ratio of sample sizes, and returns a 2-column matrix - pi.cor now has options for one-sided and two-sided prediction limits. It requires a new argument, type - pi.prop now has options for one-sided and two-sided prediction limits. It requires a new argument, type - the definition of the subscripts in the ci.2x2.mean.mixed, ci.2x2.median.mixed, and ci.2x2.stdmean.mixed functions have been changed so that the first subscript now specifies factor A and the second subscript specified factor B. - Error Corrections: - ci.2x2.stdmean.mixed -- corrected an error in the standard error computation - size.test.lc.ancova -- corrected a minor error in the sample size formula Changes in version 1.6.0 (2024-07-09) Changes: - New functions: - ci.mean.fpc -- Computes confidence interval for a mean with a finite population correction - ci.prop.fpc -- Computes confidence interval for a proportion with a finite population correction - ci.poisson -- Computes confidence interval for a Poisson rate - ci.ratio.poisson2 -- Computes confidence interval for a ratio of Poisson rates in a 2-group design - ci.bscor -- Computes confidence interval for a biserial correlation - pi.cor -- Computes prediction interval for an estimated correlation - pi.prop -- Computes prediction interval for an estimated proportion - test.cor -- Hypothesis test for a Pearson or partial correlation (for zero or non-zero null hypotheses) - test.spear -- Hypothesis test for a Spearman correlation (for zero or non-zero null hypotheses) - test.cor2 -- Hypothesis test for a 2-group Pearson or partial correlation difference - test.spear2 -- Hypothesis test for a 2-group Spearman correlation difference - test.mean -- Hypothesis test for a mean using summary information - size.ci.cor2 -- Computes sample size for a 2-group Pearson correlation difference confidence interval - size.ci.spear2 -- Computes sample size for a 2-group Spearman correlation difference confidence interval - size.ci.tetra -- Computes sample size for a tetrachoric correlation confidence interval - size.ci.mean.prior -- Computes sample size for a mean confidence interval using a planning value from a prior study - size.ci.prop.prior -- Computes sample size for a proportion confidence interval using a planning value from a prior study - size.ci.cor.prior -- Computes sample size for a correlation confidence interval using a planning value from a prior study - adj.se -- Computes adjusted standard errors for slope coefficients in an exploratory analysis - fitindices -- Computes four SEM fit indices - Modifications: - ci.var.upper now computes an exact upper limit rather than an approximate upper limit - power computations are now more accurate for very small effect sizes in the power.cor, power.cor2, power.lc.meanc.bs, power.mean, power.mean2, power.mean.ps, power.prop, power.pro2, and power.prop.ps functions - size.test.prop and size.test.prop2 now assume the test statistic will use a continuity correction - one-group function names that end with a "1" have been renamed and now exclude the "1" (for naming consistency and to avoid confusion with lower case L). - ci.mape2 has been renamed ci.ratio.mape2, and ci.cod2 has been renamed ci.ratio.cod2 - The ci.phi function now uses a Fisher transformation for improved coverage probability performance - Deletions: - size.test.slope.gen removed Changes in version 1.5.0 (2023-12-20) Changes: - New functions: - ci.cv1 -- Computes confidence interval for a coefficient of variation - ci.ratio.cv2 -- Computes confidence interval for a ratio of coefficients of variation - ci.pv -- Computes confidence intervals for positive and negative predictive values with retrospective sampling - ci.2x2.stdmean.ws -- Computes confidence intervals of standardized effects in a 2x2 within-subjects design - ci.2x2.stdmean.mixed -- Computes confidence intervals of standardized effects in a 2x2 mixed design - ci.2x2.median.ws -- Computes confidence intervals of effects in a 2x2 within-subjects design for medians - ci.2x2.median.mixed -- Computes confidence intervals of effects in a 2x2 mixed design for medians - spearmanbrown -- Computes the reliability of a scale with r2 measurements given the reliability of a scale with r1 measurements - size.ci.spear -- Computes the sample size requirement for a Spearman correlation confidence interval - size.ci.pbcor -- Computes the sample size requirement for a point-biserial correlation confidence interval - size.ci.mape1 -- Computes the sample size requirement for a mean absolute prediction error confidence interval - Error Corrections: - ci.cramer -- corrected an error in the CI computation - ci.lc.stdmean.ws -- corrected an error in the standard error computation - Modifications: - both biased and bias adjusted estimates are now reported in ci.stdmean1, ci.stdmean2, ci.stdmean.ps, ci.stdmean.strat, and ci.2x2.stdmean.bs - ci.mape has been renamed ci.mape1 Changes in version 1.4.0 (2023-06-14) Changes: - New functions: - power.prop1 -- Computes power for 1-sample test of proportion for a planned sample size - power.prop2 -- Computes power for 2-sample test of proportion for planned sample sizes - power.prop.ps -- Computes power for paired-samples test of proportion for a planned sample size - power.mean1 -- Computes power for 1-sample t-test for a planned sample size - power.mean2 -- Computes power for 2-sample t-test for planned sample sizes - power.mean.ps -- Computes power for paired-samples t-test for a planned sample size - power.lc.mean.bs -- Computes power of a test for a linear contrast of means for planned sample sizes in a between-subjects design - power.cor1 -- Computes power for 1-sample test of correlation for a planned sample size - power.cor2 -- Computes power for 2-sample test of correlations for planned sample sizes - ci.cqv1 -- Computes confidence interval for a population coefficient of qualitative variation - ci.prop1.inv -- Computes confidence interval for a population proportion using inverse sampling - ci.prop2.inv -- Computes confidence interval for a difference in population proportions using inverse sampling - ci.agree.3rater -- Computes confidence intervals for a 3-rater design with dichotomous ratings - ci.ratio.sd2 -- Computes robust confidence interval for ratio of standard deviations in a 2-group design - size.test.cor2 -- Computes sample size for a test of equal Pearson or partial correlation in a 2-group design - size.test.cronbach2 -- Computes sample size to test equality of Cronbach reliability coefficients in a 2-group design - size.ci.cronbach2 -- Computes sample size for a 2-group Cronbach reliability difference confidence interval - size.ci.etasqr -- Computes sample size for an eta-squared confidence interval - size.ci.indirect -- Computes sample size for an indirect effect confidence interval - ci.mape2 -- Computes confidence interval for a ratio of mean absolute prediction errors in a 2-group design - ci.rel2 -- Computes confidence interval for a 2-group reliability difference - ci.cronbach2 -- Computes confidence interval for a difference in Cronbach reliabilities in a 2-group design - ci.2x2.stdmean.bs -- Computes confidence intervals of standardized effects in a 2x2 between-subjects design for means - ci.2x2.median.bs -- Computes confidence intervals of effects in a 2x2 between-subjects design for medians - pi.var.upper -- Computes upper prediction limit for an estimated variance - ci.bayes.normal -- Computes Bayesian credible interval for any parameter estimator with a normal sampling distributuion using a Normal prior distribution - ci.bayes.prop1 -- Computes Bayesian credible interval for a single proportion using a Beta prior distribution - Modifications: - Corrected Example output in ci.reliability and ci.prop.ps - SE added to output in: ci.cronbach, ci.oddsratio, ci.yule, ci.etasqr, ci.rsqr, ci.spear2, ci.cor2, ci.cor.dep, ci.cod1, ci.mad1, ci.mape, ci.agree2, ci.pbcor, and ci.tetra - Improved accuracy in size.ci.rsqr - Three generalized Yule coefficients added to ci.yule - The ci.prop.ps, ci.ratio.prop.ps, and ci.2x2.prop.mixed functions now define proportions for the y = 1 category rather than the y = 0 category. Changes in version 1.3.0 (2023-01-11) Changes: - New functions: - ci.theil -- Theil-Sen estimate and confidence interval for slope - sim.ci.median2 -- Simulates confidence interval coverage probability for a median difference in a two-group design - sim.ci.median.ps -- Simulates confidence interval coverage probability for a median difference in a paired design - sim.ci.stdmean2 -- Simulates confidence interval coverage probability for a standardized mean difference in a two-group design - pi.score.ps -- Prediction interval for difference of scores in a 2-level within-subjects experiment - Updated outputs: - ci.cod1 -- first column is 'Estimate', no longer 'COD' - ci.cod2 -- first column is 'Estimate', no longer 'COD1' - ci.cramer -- first column is 'Estimate', no longer 'Cramer's V' - ci.lc.stdmean.bs -- now returns 3 rows, adding sample size for group 1 standardizer - ci.lc.stdmean.ws -- now returns two rows, one for each standardizer - ci.mad1 -- first column is 'Estimate', no longer 'MAD' - ci.mape -- first column is 'Estimate', no longer 'MAPE' - size.ci.lc.stdmean.bs -- now returns two rows, one for each standardizer - size.ci.lc.stdmean.ws -- now returns two rows, one for each standardizer - size.ci.stdmean2 -- now returns two rows, one for each standardizer - size.ci.stdmean.ps -- now returns two rows, one for each standardizer - ci.mann -- now returns a confidence interval for P(y1 > y2) rather than P(y1 < y2). Changes in version 1.2.0 (2022-08-19) Changes: - New functions: - ci.cramer - Confidence interval for Cramer's V - ci.2x2.mean.bs - Confidence intervals for effects in a 2x2 between-subjects design for means - ci.2x2.mean.ws - Confidence intervals for effects in a 2x2 within-subjects design for means - ci.2x2.mean.mixed - Confidence intervals for effects in a 2x2 mixed design for means - ci.2x2.prop.bs - Confidence intervals for effects in a 2x2 between-subjects design for proportions - ci.2x2.prop.mixed - Confidence intervals for effects in a 2x2 mixed design for proportions - sim.ci.mean1 – Simulation of confidence interval for a mean - sim.ci.mean2 – Simulation of confidence interval for mean difference in a two-group design - sim.ci.mean.ps – Simulation of confidence interval for mean difference in a paired-samples design - sim.ci.median1 – Simulation of confidence interval for a single median - sim.ci.cor – Simulation of confidence interval for a Pearson correlation - sim.ci.spear – Simulation of confidence interval for a Spearman correlation - Modifications: - The ci.prop.ps function now outputs an adjusted point estimate of the proportion difference, as stated in the documentation, rather than an unadjusted estimate - The ci.cor, ci.cor2, and ci.cor.dep functions now uses a bias adjustment to reduce the bias of the Fisher transformed correlations - The ci.median1 function now uses the same standard error formula as the ci.median2, ci.ratio.median2, and ci.median.ps functions - Error Correction: - ci.indirect -- Corrected an error in the standard error computation Changes in version 1.1.0 (2022-06-22) Changes: - New functions: - ci.agree2 - Confidence interval for G-index difference in a 2-group design - ci.cod2 - Confidence interval for a ratio of dispersion coefficients in a 2-group - ci.etasqr - Confidence interval for eta-squared - ci.lc.gen.bs - Confidence interval for a linear contrast of parameters in a between-subjects design - ci.lc.glm - Confidence interval for a linear contrast of general linear model parameters - ci.reliability - Confidence interval for a reliability coefficient - ci.rsqr - Confidence interval for squared multiple correlation - ci.sign1 - Confidence interval for the parameter of the one-sample sign test - ci.slope.mean.bs - Confidence interval for the slope of means in a single-factor design with a quantitative between-subjects factor - test.kurtosis - Computes Monte Carlo p-value for test of excess kurtosis - test.skew - Computes Monte Carlo p-value for test of skewness - test.mono.mean.bs - Test of a monotonic trend in means for an ordered between-subjects factor - test.mono.prop.bs - Test of monotonic trend in proportions for an ordered between-subjects - etasqr.gen.2way - Computes generalized eta-squared estimates in a two-factor design - Updated documentation for consistency - Changed arguments for some functions for consistency - size.test.cronbach now takes (alpha, pow, rel, r, h) rather than (alpha, pow, rel, a, h) - ci.cronbach now takes (alpha, rel, r, n) rather than (alpha, rel, a, n) - Changed some of the column names in returned matrixes for consistency: - ci.median.ps, the last column is now "COV" rather than "cov" Changes in version 1.0.0 (2021-09-09) - Initial release