conf.limits.ncf {MBESS}R Documentation

Confidence limits for noncentral F parameters

Description

Function to determine the noncentral parameter that leads to the observed F-value, so that a confidence interval around the population F-value can be conducted. Used for forming confidence intervals around noncentral parameters (given the monotonic relationship between the F-value and the noncentral value).

Usage

conf.limits.ncf(F.value = NULL, conf.level = .95, df.1 = NULL, 
df.2 = NULL, alpha.lower = NULL, alpha.upper = NULL, tol = 1e-09,
Jumping.Prop = 0.1)

Arguments

F.value the observed F-value
conf.level the desired degree of confidence for the interval
df.1 the numerator degrees of freedom
df.2 the denominator degrees of freedom
alpha.lower Type I error for the lower confidence limit
alpha.upper Type I error for the upper confidence limit
tol tolerance for iterative convergence
Jumping.Prop Value used in the iterative scheme to determine the noncentral parameters necessary for confidence interval construction using noncentral F-distributions (0 < Jumping.Prop < 1)

Details

This function is the relied upon by the ci.R2 and ss.aipe.R2. If the function fails (or if a function relying upon this function fails), adjust the Jumping.Prop (to a smaller value).

Value

Lower.Limit Value of the distribution with Lower.Limit noncentral value that has at its specified quantile F.value
Prob.Less.Lower Proportion of cases falling below Lower.Limit
Upper.Limit Value of the distribution with Upper.Limit noncentral value that has at its specified quantile F.value
Prob.Greater.Upper Proportion of cases falling above Upper.Limit

Author(s)

Ken Kelley (University of Notre Dame; KKelley@ND.Edu)

See Also

ss.aipe.R2, ci.R2, conf.limits.nct

Examples

conf.limits.ncf(F.value = 5, conf.level = .95, df.1 = 5, 
df.2 = 100)

# A one sided confidence interval.
conf.limits.ncf(F.value = 5, conf.level = NULL, df.1 = 5, 
df.2 = 100, alpha.lower = .05, alpha.upper = 0, tol = 1e-09,
Jumping.Prop = 0.1)

[Package MBESS version 2.0.0 Index]