conf.limits.ncf {MBESS} | R Documentation |
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).
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)
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 ) |
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).
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 |
Ken Kelley (University of Notre Dame; KKelley@ND.Edu)
ss.aipe.R2
, ci.R2
, conf.limits.nct
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)