FcnsByCatPower: 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
ll{
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
ll{
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
ll{
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
ll{
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
ll{
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
ll{
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.
}