# conf.limits.ncf: Confidence limits for noncentral F parameters In MBESS: The MBESS R Package

 conf.limits.ncf 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`) (users should not need to change this value)

### 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); Keke Lai (University of Califonia-Merced)

`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)
``````

MBESS documentation built on Oct. 26, 2023, 9:07 a.m.