conf.limits.nc.chisq

Chi.Square

the desired degree of confidence for the interval

conf.level

Type I error for the lower confidence limit

alpha.lower

Type I error for the upper confidence limit

alpha.upper

Value used in the iterative scheme to determine the noncentral 
  parameters necessary for confidence interval construction using noncentral 
  chi square-distributions (<code>0 < Jumping.Prop < 1</code>)

Jumping.Prop


Function to determine the noncentral parameter that leads to the observed <code>Chi.Square</code>-value, 
so that a confidence interval for the population noncentral chi-squrae value can be formed.


multivariate

regression

design

Implements methods that useful in designing research and analyzing data, with
particular emphasis on methods that are developed for or used within the behavioral,
educational, and social sciences (broadly defined). That being said, many of the methods
implemented within MBESS are applicable to a wide variety of disciplines. MBESS has a
suite of functions for a variety of related topics, such as effect sizes, confidence intervals
for effect sizes (including standardized effect sizes and noncentral effect sizes), sample size
planning (from the accuracy in parameter estimation [AIPE], power analytic, equivalence, and
minimum-risk point estimation perspectives), mediation analysis, various properties of
distributions, and a variety of utility functions. MBESS (pronounced 'em-bes') was originally
an acronym for 'Methods for the Behavioral, Educational, and Social Sciences,' but at this
point MBESS contains methods applicable and used in a wide variety of fields and is an
orphan acronym, in the sense that what was an acronym is now literally its name. MBESS has
greatly benefited from others, see <http://nd.edu/~kkelley/site/MBESS.html> for a detailed
list of those that have contributed and other details.

conf.limits.nc.chisq: Confidence limits for noncentral chi square parameters

Description

Usage

Arguments

Value

Details

See Also

Examples