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statpsych version 1.9.0 (Release date: 2026/01/01)

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

statpsych version 1.8.0 (Release date: 2025/06/06)

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

statpsych version 1.7.0 (Release date: 2024/12/17)

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

statpsych version 1.6.0 (Release date: 2024/07/08)

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

statpsych version 1.5.0 (Release date: 2023/12/11)

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

statpsych version 1.4.0 (Release date: 2023/06/26)

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.

statpsych v1.3.0 (Release date: 2023/01/01)

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).

statpsych v1.2.0 (Release date: 2022/08/15)

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

statpsych v1.1.0 (Release date: 2022/06/30)

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”

statpsych 1.0.0 (Release date: 2021/09/09)

Initial release

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