joint.ci.bonf: Calculates joint confidence intervals for parameters in...

In asbio: A Collection of Statistical Tools for Biologists

Calculates joint confidence intervals for parameters in linear models using a Bonferroni procedure.

Description

Creates widened confidence intervals to allow joint consideration of parameter confidence intervals.

Usage

joint.ci.bonf(model, conf = 0.95)

Arguments

model	A linear model created by lm
conf	level of confidence 1 - P(type I error)

Details

As with all Bonferroni-based methods for joint confidence the resulting intervals are exceedingly conservative and thus are prone to type II error.

Value

Returns a dataframe with the upper and lower confidence bounds for each parameter in a linear model.

Author(s)

Ken Aho

References

Kutner, M. H., Nachtsheim, C. J., Neter, J., and W. Li. (2005) Applied Linear Statistical Models, 5th edition. McGraw-Hill, Boston.

See Also

confint, p.adjust

Examples

Soil.C<-c(13,20,10,11,2,25,30,25,23)
Soil.N<-c(1.2,2,1.5,1,0.3,2,3,2.7,2.5)
Slope<-c(15,14,16,12,10,18,25,24,20)
Aspect<-c(45,120,100,56,5,20,5,15,15)
Y<-as.vector(c(20,30,10,15,5,45,60,55,45))
model<-lm(Y~Soil.C+Soil.N+Slope+Aspect)
joint.ci.bonf(model)

asbio documentation built on May 29, 2024, 5:57 a.m.