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
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)