FcnsByCatPower: EnvStats Functions for Power and Sample Size Calculations
In EnvStats: Package for Environmental Statistics, Including US EPA Guidance

FcnsByCatPower

R Documentation

EnvStats Functions for Power and Sample Size Calculations

Description

The EnvStats functions listed below are useful for power and sample size calculations.

Details

Confidence Intervals

Function Name	Description
`ciTableProp`	Confidence intervals for binomial proportion, or
	difference between two proportions, following Bacchetti (2010)
`ciBinomHalfWidth`	Compute the half-width of a confidence interval for a
	Binomial proportion or the difference between two proportions.
`ciBinomN`	Compute the sample size necessary to achieve a specified
	half-width of a confidence interval for a Binomial proportion or
	the difference between two proportions.
`plotCiBinomDesign`	Create plots for a sampling design based on a confidence interval
	for a Binomial proportion or the difference between two proportions.
`ciTableMean`	Confidence intervals for mean of normal distribution, or
	difference between two means, following Bacchetti (2010)
`ciNormHalfWidth`	Compute the half-width of a confidence interval for the mean of a
	Normal distribution or the difference between two means.
`ciNormN`	Compute the sample size necessary to achieve a specified half-width
	of a confidence interval for the mean of a Normal distribution or
	the difference between two means.
`plotCiNormDesign`	Create plots for a sampling design based on a confidence interval
	for the mean of a Normal distribution or the difference between
	two means.
`ciNparConfLevel`	Compute the confidence level associated with a nonparametric
	confidence interval for a percentile.
`ciNparN`	Compute the sample size necessary to achieve a specified
	confidence level for a nonparametric confidence interval for
	a percentile.
`plotCiNparDesign`	Create plots for a sampling design based on a nonparametric
	confidence interval for a percentile.

Hypothesis Tests

Function Name	Description
`aovN`	Compute the sample sizes necessary to achieve a
	specified power for a one-way fixed-effects analysis
	of variance test.
`aovPower`	Compute the power of a one-way fixed-effects analysis of
	variance test.
`plotAovDesign`	Create plots for a sampling design based on a one-way
	analysis of variance.
`propTestN`	Compute the sample size necessary to achieve a specified
	power for a one- or two-sample proportion test.
`propTestPower`	Compute the power of a one- or two-sample proportion test.
`propTestMdd`	Compute the minimal detectable difference associated with
	a one- or two-sample proportion test.
`plotPropTestDesign`	Create plots involving sample size, power, difference, and
	significance level for a one- or two-sample proportion test.
`tTestAlpha`	Compute the Type I Error associated with specified values for
	for power, sample size(s), and scaled MDD for a one- or
	two-sample t-test.
`tTestN`	Compute the sample size necessary to achieve a specified
	power for a one- or two-sample t-test.
`tTestPower`	Compute the power of a one- or two-sample t-test.
`tTestScaledMdd`	Compute the scaled minimal detectable difference
	associated with a one- or two-sample t-test.
`plotTTestDesign`	Create plots for a sampling design based on a one- or
	two-sample t-test.
`tTestLnormAltN`	Compute the sample size necessary to achieve a specified
	power for a one- or two-sample t-test, assuming lognormal
	data.
`tTestLnormAltPower`	Compute the power of a one- or two-sample t-test, assuming
	lognormal data.
`tTestLnormAltRatioOfMeans`	Compute the minimal or maximal detectable ratio of means
	associated with a one- or two-sample t-test, assuming
	lognormal data.
`plotTTestLnormAltDesign`	Create plots for a sampling design based on a one- or
	two-sample t-test, assuming lognormal data.
`linearTrendTestN`	Compute the sample size necessary to achieve a specified
	power for a t-test for linear trend.
`linearTrendTestPower`	Compute the power of a t-test for linear trend.
`linearTrendTestScaledMds`	Compute the scaled minimal detectable slope for a t-test
	for linear trend.
`plotLinearTrendTestDesign`	Create plots for a sampling design based on a t-test for
	linear trend.

Prediction Intervals

Normal Distribution Prediction Intervals

Function Name	Description
`predIntNormHalfWidth`	Compute the half-width of a prediction
	interval for a normal distribution.
`predIntNormK`	Compute the required value of `K` for
	a prediction interval for a Normal
	distribution.
`predIntNormN`	Compute the sample size necessary to
	achieve a specified half-width for a
	prediction interval for a Normal
	distribution.
`plotPredIntNormDesign`	Create plots for a sampling design
	based on the width of a prediction
	interval for a Normal distribution.
`predIntNormTestPower`	Compute the probability that at least
	one future observation (or mean)
	falls outside a prediction interval
	for a Normal distribution.
`plotPredIntNormTestPowerCurve`	Create plots for a sampling
	design based on a prediction interval
	for a Normal distribution.
`predIntNormSimultaneousTestPower`	Compute the probability that at
	least one set of future observations
	(or means) violates the given rule
	based on a simultaneous prediction
	interval for a Normal distribution.
`plotPredIntNormSimultaneousTestPowerCurve`	Create plots for a sampling design
	based on a simultaneous prediction
	interval for a Normal distribution.

Lognormal Distribution Prediction Intervals

Function Name	Description
`predIntLnormAltTestPower`	Compute the probability that at least
	one future observation (or geometric
	mean) falls outside a prediction
	interval for a lognormal distribution.
`plotPredIntLnormAltTestPowerCurve`	Create plots for a sampling design
	based on a prediction interval for a
	lognormal distribution.
`predIntLnormAltSimultaneousTestPower`	Compute the probability that at least
	one set of future observations (or
	geometric means) violates the given
	rule based on a simultaneous
	prediction interval for a lognormal
	distribution.
`plotPredIntLnormAltSimultaneousTestPowerCurve`	Create plots for a sampling design
	based on a simultaneous prediction
	interval for a lognormal distribution.

Nonparametric Prediction Intervals

Function Name	Description

`predIntNparConfLevel`	Compute the confidence level associated with
	a nonparametric prediction interval.
`predIntNparN`	Compute the required sample size to achieve
	a specified confidence level for a
	nonparametric prediction interval.
`plotPredIntNparDesign`	Create plots for a sampling design based on
	the confidence level and sample size of a
	nonparametric prediction interval.
`predIntNparSimultaneousConfLevel`	Compute the confidence level associated with
	a simultaneous nonparametric prediction
	interval.
`predIntNparSimultaneousN`	Compute the required sample size for a
	simultaneous nonparametric prediction
	interval.
`plotPredIntNparSimultaneousDesign`	Create plots for a sampling design based on
	a simultaneous nonparametric prediction
	interval.
`predIntNparSimultaneousTestPower`	Compute the probability that at least one
	set of future observations violates the
	given rule based on a nonparametric
	simultaneous prediction interval.
`plotPredIntNparSimultaneousTestPowerCurve`	Create plots for a sampling design based on
	a simultaneous nonparametric prediction
	interval.

Tolerance Intervals

Function Name	Description
`tolIntNormHalfWidth`	Compute the half-width of a tolerance
	interval for a normal distribution.
`tolIntNormK`	Compute the required value of `K` for a
	tolerance interval for a Normal distribution.
`tolIntNormN`	Compute the sample size necessary to achieve a
	specified half-width for a tolerance interval
	for a Normal distribution.
`plotTolIntNormDesign`	Create plots for a sampling design based on a
	tolerance interval for a Normal distribution.

`tolIntNparConfLevel`	Compute the confidence level associated with a
	nonparametric tolerance interval for a specified
	sample size and coverage.
`tolIntNparCoverage`	Compute the coverage associated with a
	nonparametric tolerance interval for a specified
	sample size and confidence level.
`tolIntNparN`	Compute the sample size required for a nonparametric
	tolerance interval with a specified coverage and
	confidence level.
`plotTolIntNparDesign`	Create plots for a sampling design based on a
	nonparametric tolerance interval.