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 2-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.cramer – first column is ‘Estimate’, no longer ‘Cramer’s V’
- ci.mad1 – first column is ‘Estimate’, no longer ‘MAD’
- ci.mape – first column is ‘Estimate’, no longer ‘MAPE’
- ci.lc.stdmean.bs – now returns 3 rows, adding results for group 1 standardizer
- ci.lc.stdmean.ws – now returns two rows, adding results for level 1 standardizer
- size.ci.lc.stdmean.bs – now returns two rows, adding result for group 1 standardizer
- size.ci.lc.stdmean.ws – now returns two rows, adding result for level 1 standardizer
- size.ci.stdmean2 – now returns two rows, adding result for group 1 standardizer
- size.ci.stdmean.ps – now returns two rows, adding result for level 1 standardizer
- ci.mann – now returns a confidence interval for P(y1 > y2) rather than P(y1 < y2).

- Error correction:
- ci.lc.std.mean.ws – corrected an error in the standard error

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 single 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:
- Corrected an error for the standard error computation in the ci.indirect function

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”

- Initial release