Function reference • statpsych

Confidence intervals Confidence intervals for different effect sizes and designs
`ci.2x2.mean.bs()`	Computes tests and confidence intervals of effects in a 2x2 between-subjects design for means
`ci.2x2.mean.mixed()`	Computes tests and confidence intervals of effects in a 2x2 mixed design for means
`ci.2x2.mean.ws()`	Computes tests and confidence intervals of effects in a 2x2 within-subjects design for means
`ci.2x2.median.bs()`	Computes tests and confidence intervals of effects in a 2x2 betwen-subjects design for medians
`ci.2x2.median.mixed()`	Computes confidence intervals in a 2x2 mixed design for medians
`ci.2x2.median.ws()`	Computes confidence intervals in a 2x2 within-subjects design for medians
`ci.2x2.prop.bs()`	Computes tests and confidence intervals of effects in a 2x2 between- subjects design for proportions
`ci.2x2.prop.mixed()`	Computes tests and confidence intervals of effects in a 2x2 mixed factorial design for proportions
`ci.2x2.stdmean.bs()`	Computes confidence intervals of standardized effects in a 2x2 between-subjects design for means
`ci.2x2.stdmean.mixed()`	Computes confidence intervals of standardized effects in a 2x2 mixed design
`ci.2x2.stdmean.ws()`	Computes confidence intervals of standardized effects in a 2x2 within-subjects design
`ci.agree.3rater()`	Computes confidence intervals for a 3-rater design with dichotomous ratings
`ci.agree()`	Confidence interval for a G-index of agreement
`ci.agree2()`	Confidence interval for G-index difference in a 2-group design
`ci.bayes.normal()`	Bayesian credible interval for a normal prior distribution
`ci.bayes.prop1()`	Bayesian credible interval for a single proportion
`ci.biphi()`	Confidence interval for a biserial-phi correlation
`ci.cod1()`	Confidence interval for a single coefficient of dispersion
`ci.cod2()`	Confidence interval for a ratio of dispersion coefficients in a 2-group design
`ci.condslope.log()`	Confidence interval for conditional (simple) slopes in a logistic model
`ci.condslope()`	Confidence interval for conditional (simple) slopes in a linear model
`ci.cor.dep()`	Confidence interval for a difference in dependent Pearson correlations
`ci.cor()`	Confidence interval for a Pearson or partial correlation
`ci.cor2.gen()`	Confidence interval for a 2-group correlation difference
`ci.cor2()`	Confidence interval for a 2-group Pearson correlation difference
`ci.cqv1()`	Confidence interval for a single coefficient of quartile variation
`ci.cramer()`	Confidence interval for Cramer's V
`ci.cronbach()`	Confidence interval for a Cronbach reliability
`ci.cronbach2()`	Confidence interval for a difference in Cronbach reliabilities in a 2-group design
`ci.cv1()`	Confidence interval for a single coefficient of variation
`ci.etasqr()`	Confidence interval for eta-squared
`ci.fisher()`	Fisher confidence interval
`ci.indirect()`	Confidence interval for an indirect effect
`ci.kappa()`	Confidence interval for a kappa reliability
`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.lc.mean.bs()`	Confidence interval for a linear contrast of means in a between-subjects design
`ci.lc.median.bs()`	Confidence interval for a linear contrast of medians in a between-subjects design
`ci.lc.prop.bs()`	Confidence interval for a linear contrast of proportions in a between- subjects design
`ci.lc.reg()`	Confidence interval for a linear contrast of regression coefficients in multiple group regression model
`ci.lc.stdmean.bs()`	Confidence interval for a standardized linear contrast of means in a between-subjects design
`ci.lc.stdmean.ws()`	Confidence interval for a standardized linear contrast of means in a within-subjects design
`ci.mad1()`	Confidence interval for a single mean absolute deviation
`ci.mann()`	Confidence interval for a Mann-Whitney parameter
`ci.mape1()`	Confidence interval for a mean absolute prediction error
`ci.mape2()`	Confidence interval for a ratio of mean absolute prediction errors in a 2-group design
`ci.mean.ps()`	Confidence interval for a paired-samples mean difference
`ci.mean1()`	Confidence interval for a single mean
`ci.mean2()`	Confidence interval for a 2-group mean difference
`ci.median.ps()`	Confidence interval for a paired-samples median difference
`ci.median1()`	Confidence interval for a single median
`ci.median2()`	Confidence interval for a 2-group median difference
`ci.oddsratio()`	Confidence interval for an odds ratio
`ci.pairs.prop.bs()`	Bonferroni confidence intervals for all pairwise proportion differences in a between-subjects design
`ci.pairs.prop1()`	Confidence intervals for pairwise proportion differences of a polychotomous variable
`ci.pbcor()`	Confidence interval for a point-biserial correlation
`ci.phi()`	Confidence interval for a phi correlation
`ci.popsize()`	Confidence interval for an unknown population size
`ci.prop.ps()`	Confidence interval for a paired-samples proportion difference
`ci.prop1.inv()`	Confidence interval for a single proportion using inverse sampling
`ci.prop1()`	Confidence interval for a single proportion
`ci.prop2.inv()`	Confidence interval for a 2-group proportion difference using inverse sampling
`ci.prop2()`	Confidence interval for a 2-group proportion difference
`ci.pv()`	Confidence intervals for positive and negative predictive values with retrospective sampling
`ci.random.anova1()`	Confidence intervals for parameters of one-way random effects ANOVA
`ci.ratio.cv2()`	Confidence interval for a ratio of coefficients of variation in a 2-group design
`ci.ratio.mad.ps()`	Confidence interval for a paired-sample MAD ratio
`ci.ratio.mad2()`	Confidence interval for a 2-group ratio of mean absolute deviations
`ci.ratio.mean.ps()`	Confidence interval for a paired-samples mean ratio
`ci.ratio.mean2()`	Confidence interval for a 2-group mean ratio
`ci.ratio.median.ps()`	Confidence interval for a paired-samples median ratio
`ci.ratio.median2()`	Confidence interval for a 2-group median ratio
`ci.ratio.prop.ps()`	Confidence interval for a paired-samples proportion ratio
`ci.ratio.prop2()`	Confidence interval for a 2-group proportion ratio
`ci.ratio.sd2()`	Confidence interval for a 2-group ratio of standard deviations
`ci.rel2()`	Confidence interval for a 2-group reliability difference
`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
`ci.slope.prop.bs()`	Confidence interval for a slope of a proportion in a single-factor design with a quantitative between-subjects factor
`ci.spcor()`	Confidence interval for a semipartial correlation
`ci.spear()`	Confidence interval for a Spearman correlation
`ci.spear2()`	Confidence interval for a 2-group Spearman correlation difference
`ci.stdmean.ps()`	Confidence interval for a paired-samples standardized mean difference
`ci.stdmean.strat()`	Confidence interval for a 2-group standardized mean difference with stratified sampling
`ci.stdmean1()`	Confidence interval for a single standardized mean
`ci.stdmean2()`	Confidence interval for a 2-group standardized mean difference
`ci.tetra()`	Confidence interval for a tetrachoric correlation
`ci.theil()`	Theil-Sen estimate and confidence interval for slope
`ci.tukey()`	Tukey-Kramer confidence intervals for all pairwise mean differences in a betwen-subjects design
`ci.var.upper()`	Upper confidence limit of variance
`ci.yule()`	Confidence intervals for generalized Yule coefficients
Miscellaneous Other functions, including functions for simulating data
`etasqr.gen.2way()`	Generalized eta-squared estimates in a two-factor design
`etasqr.adj()`	Bias adjusts an eta-squared estimate
`iqv()`	Indices of qualitative variation
`pi.score1()`	Prediction interval for one score
`pi.score2()`	Prediction interval for a difference of scores in a 2-group experiment
`random.sample()`	Generate a random sample
`random.y()`	Generate random sample of scores
`random.yx()`	Generates random bivariate scores
`randomize()`	Randomize a sample into groups
`slope.contrast()`	Contrast coefficients for the slope of a quantitative factor
`spearmanbrown()`	Computes the reliability of a scale with r2 measurements given the reliability of a scale with r1 measurements
Power Compute power for a given sample size for various designs
`power.cor1()`	Approximates the power of a correlation test for a planned sample size
`power.cor2()`	Approximates the power of a test for equal correlations in a 2-group design for planned sample sizes
`power.lc.mean.bs()`	Approximates the power of a test for a linear contrast of means for planned sample sizes in a between-subjects design
`power.mean.ps()`	Approximates the power of a paired-samples t-test for a planned sample size
`power.mean1()`	Approximates the power of a one-sample t-test for a planned sample size
`power.mean2()`	Approximates the power of a two-sample t-test for planned sample sizes
`power.prop.ps()`	Approximates the power of a paired-samples test of equal porportions for a planned sample size
`power.prop1()`	Approximates the power of a one-sample proportion test for a planned sample size
`power.prop2()`	Approximates the power of a two-sample proportion test for planned sample sizes
Prediction intervals Prediction intervals
`pi.score.ps()`	Prediction interval for difference of scores in a 2-level within-subjects experiment
`pi.score1()`	Prediction interval for one score
`pi.score2()`	Prediction interval for a difference of scores in a 2-group experiment
`pi.var.upper()`	Upper prediction limit for an estimated variance
Sample-size planning Sample sizes for desired precision or power
`size.ci.agree()`	Sample size for a G-index confidence interval
`size.ci.condmean()`	Sample size for a conditional mean confidence interval
`size.ci.cor()`	Sample size for a Pearson or partial correlation confidence interval
`size.ci.cronbach()`	Sample size for a Cronbach reliability confidence interval
`size.ci.cronbach2()`	Sample size for a 2-group Cronbach reliability difference confidence interval
`size.ci.etasqr()`	Sample size for an eta-squared confidence interval
`size.ci.indirect()`	Sample size for an indirect effect confidence interval
`size.ci.lc.ancova()`	Sample size for a linear contrast confidence interval in an ANCOVA
`size.ci.lc.mean.bs()`	Sample size for a between-subjects mean linear contrast confidence interval
`size.ci.lc.mean.ws()`	Sample size for a within-subjects mean linear contrast confidence interval
`size.ci.lc.prop.bs()`	Sample size for a between-subjects proportion linear contrast confidence interval
`size.ci.lc.stdmean.bs()`	Sample size for a between-subjects standardized linear contrast of means confidence interval
`size.ci.lc.stdmean.ws()`	Sample size for a within-subjects standardized linear contrast of means confidence interval
`size.ci.mape1()`	Sample size for a mean absolute prediction error confidence interval
`size.ci.mean.ps()`	Sample size for a paired-samples mean difference confidence interval
`size.ci.mean1()`	Sample size for a single mean confidence interval
`size.ci.mean2()`	Sample size for a 2-group mean difference confidence interval
`size.ci.pbcor()`	Sample size for a point-biserial correlation confidence interval
`size.ci.prop.ps()`	Sample size for a paired-sample proportion difference confidence interval
`size.ci.prop1()`	Sample size for a single proportion confidence interval
`size.ci.prop2()`	Sample size for a 2-group proportion difference confidence interval
`size.ci.ratio.mean.ps()`	Sample size for a paired-samples mean ratio confidence interval
`size.ci.ratio.mean2()`	Sample size for a 2-group mean ratio confidence interval
`size.ci.ratio.prop.ps()`	Sample size for a paired-samples proportion ratio confidence interval
`size.ci.ratio.prop2()`	Sample size for a 2-group proportion ratio confidence interval
`size.ci.rsqr()`	Sample size for a squared multiple correlation confidence interval
`size.ci.second()`	Sample size for a second-stage confidence interval
`size.ci.slope()`	Sample size for a slope confidence interval
`size.ci.spear()`	Sample size for a Spearman correlation confidence interval
`size.ci.stdmean.ps()`	Sample size for a paired-samples standardized mean difference confidence interval
`size.ci.stdmean2()`	Sample size for a 2-group standardized mean difference confidence interval
`size.equiv.mean.ps()`	Sample size for a paired-samples mean equivalence test
`size.equiv.mean2()`	Sample size for a 2-group mean equivalence test
`size.equiv.prop.ps()`	Sample size for a paired-samples proportion equivalence test
`size.equiv.prop2()`	Sample size for a 2-group proportion equivalence test
`size.interval.cor()`	Sample size for a finite interval test of a Pearson or partial correlation
`size.supinf.mean.ps()`	Sample size for a paired-samples mean superiority or noninferiority test
`size.supinf.mean2()`	Sample size for a 2-group mean superiority or noninferiority test
`size.supinf.prop.ps()`	Sample size for a paired-samples superiority or inferiority test of proportions
`size.supinf.prop2()`	Sample size for a 2-group superiority or inferiority test of proportions
`size.test.cor()`	Sample size for a test of a Pearson or partial correlation
`size.test.cor2()`	Sample size for a test of equal Pearson or partial correlation in a 2-group design
`size.test.cronbach()`	Sample size to test a Cronbach reliability
`size.test.cronbach2()`	Sample size to test equality of Cronbach reliability coefficients in a 2-group design
`size.test.lc.ancova()`	Sample size for a mean linear contrast test in an ANCOVA
`size.test.lc.mean.bs()`	Sample size for a test of a between-subjects mean linear contrast
`size.test.lc.mean.ws()`	Sample size for a test of a within-subjects mean linear contrast
`size.test.lc.prop.bs()`	Sample size for a test of between-subjects proportion linear contrast
`size.test.mann()`	Sample size for a Mann-Whitney test
`size.test.mean.ps()`	Sample size for a test of a paired-samples mean difference
`size.test.mean1()`	Sample size for a test of a single mean
`size.test.mean2()`	Sample size for a test of a 2-group mean difference
`size.test.prop.ps()`	Sample size for a test of a paired-samples proportion difference
`size.test.prop1()`	Sample size for a test of a single proportion
`size.test.prop2()`	Sample size for a test of a 2-group proportion difference
`size.test.sign.ps()`	Sample size for a paired-samples Sign test
`size.test.sign1()`	Sample size for a 1-sample Sign test
`size.test.slope()`	Sample size for a test of a slope
Simulations Test coverage of difference confidence intervals with simulated data
`sim.ci.cor()`	Simulates confidence interval coverage probability for a Pearson correlation
`sim.ci.mean.ps()`	Simulates confidence interval coverage probability for a paired-samples mean difference
`sim.ci.mean1()`	Simulates confidence interval coverage probability for single mean
`sim.ci.mean2()`	Simulates confidence interval coverage probability for a 2-group mean difference
`sim.ci.median.ps()`	Simulates confidence interval coverage probability for a median difference in a paired-samples design
`sim.ci.median1()`	Simulates confidence interval coverage probability for single median
`sim.ci.median2()`	Simulates confidence interval coverage probability for a median difference in a 2-group design
`sim.ci.spear()`	Simulates confidence interval coverage probability for a Spearman correlation
`sim.ci.stdmean.ps()`	Simulates confidence interval coverage probability for a standardized mean difference in a paired-samples design
`sim.ci.stdmean2()`	Simulates confidence interval coverage probability for a standardized mean difference in a 2-group design
Tests Hypothesis tests
`test.anova1.bs()`	Between-subjects F statistic and eta-squared from summary information
`test.kurtosis()`	Computes p-value for test of excess kurtosis
`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 factor
`test.prop.bs()`	Hypothesis test of equal proportions in a between-subjects design
`test.prop.ps()`	Hypothesis test for a paired-samples proportion difference
`test.prop1()`	Hypothesis test for a single proportion
`test.prop2()`	Hypothesis test for a 2-group proportion difference
`test.skew()`	Computes p-value for test of skewness

Reference

Confidence intervals

Miscellaneous

Power

Prediction intervals

Sample-size planning

Simulations

Tests