MBESS (version 4.9.3)

conf.limits.ncf: 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)

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

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) (users should not need to change this value)

Author

Ken Kelley (University of Notre Dame; ); Keke Lai (University of Califonia-Merced)

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).

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)