MBESS (version 4.1.0)

ss.aipe.reg.coef: Sample size necessary for the accuracy in parameter estimation approach for a regression coefficient of interest

Description

A function used to plan sample size from the accuracy in parameter estimation approach for a regression coefficient of interest given the input specification.

Usage

ss.aipe.reg.coef(Rho2.Y_X=NULL, Rho2.j_X.without.j=NULL, p=NULL, 
b.j=NULL, width, which.width="Full", sigma.Y=1, sigma.X=1, RHO.XX=NULL, 
Rho.YX=NULL, which.predictor=NULL, Noncentral=FALSE, alpha.lower=NULL,
alpha.upper=NULL, conf.level=.95, degree.of.certainty=NULL, assurance=NULL, 
certainty=NULL, Suppress.Statement=FALSE)

Arguments

Rho2.Y_X

Population value of the squared multiple correlation coefficient

Rho2.j_X.without.j

Population value of the squared multiple correlation coefficient predicting the jth predictor variable from the remaining p-1 predictor variables

p

the number of predictor variables

b.j

the regression coefficient for the jth predictor variable (i.e., the predictor of interest)

width

the desired width of the confidence interval

which.width

which width ("Full", "Lower", or "Upper") the width refers to (at present, only "Full" can be specified)

sigma.Y

the population standard deviation of Y (i.e., the dependent variables)

sigma.X

the population standard deviation of the jth X variable (i.e., the predictor variable of interest)

RHO.XX

Population correlation matrix for the p predictor variables

Rho.YX

Population p length vector of correlation between the dependent variable (Y) and the p independent variables

which.predictor

identifies which of the p predictors is of interest

Noncentral

specify with a TRUE or FALSE statement whether or not the noncentral approach to sample size planning should be used

alpha.lower

Type I error rate for the lower confidence interval limit

alpha.upper

Type I error rate for the upper confidence interval limit

conf.level

desired level of confidence for the computed interval (i.e., 1 - the Type I error rate)

degree.of.certainty

degree of certainty that the obtained confidence interval will be sufficiently narrow

assurance

an alias for degree.of.certainty

certainty

an alias for degree.of.certainty

Suppress.Statement

TRUE/FALSE statement whether or not a sentence describing the situation defined is printed with the necessary sample size

Value

accuracy in parameter estimation to be satisfied for the confidence interval for a particular regression coefficient given the input specifications.

Details

Not all of the arguments need to be specified, only those that provide all of the necessary information so that the sample size can be determined for the conditions specified.

References

Kelley, K. & Maxwel, S. E. (2003). Sample size for Multiple Regression: Obtaining regression coefficients that are accurate, not simply significant. Psychological Methods, 8, 305--321.

See Also

ss.aipe.reg.coef.sensitivity, conf.limits.nct

Examples

## Not run: 
# # Exchangable correlation structure
# # Rho.YX <- c(.3, .3, .3, .3, .3)
# # RHO.XX <- rbind(c(1, .5, .5, .5, .5), c(.5, 1, .5, .5, .5), c(.5, .5, 1, .5, .5), 
# # c(.5, .5, .5, 1, .5), c(.5, .5, .5, .5, 1))
# # ss.aipe.reg.coef(width=.1, which.width="Full", sigma.Y=1, sigma.X=1, RHO.XX=RHO.XX,
# # Rho.YX=Rho.YX, which.predictor=1, Noncentral=FALSE, conf.level=1-.05, 
# # degree.of.certainty=NULL, Suppress.Statement=FALSE)
# 
# # ss.aipe.reg.coef(width=.1, which.width="Full", sigma.Y=1, sigma.X=1, RHO.XX=RHO.XX,
# # Rho.YX=Rho.YX, which.predictor=1, Noncentral=FALSE, conf.level=1-.05, 
# # degree.of.certainty=.85, Suppress.Statement=FALSE)
# 
# # ss.aipe.reg.coef(width=.1, which.width="Full", sigma.Y=1, sigma.X=1, RHO.XX=RHO.XX,
# # Rho.YX=Rho.YX, which.predictor=1, Noncentral=TRUE, conf.level=1-.05,
# # degree.of.certainty=NULL, Suppress.Statement=FALSE)
# 
# # ss.aipe.reg.coef(width=.1, which.width="Full", sigma.Y=1, sigma.X=1, RHO.XX=RHO.XX, 
# # Rho.YX=Rho.YX, which.predictor=1, Noncentral=TRUE, conf.level=1-.05, 
# # degree.of.certainty=.85, Suppress.Statement=FALSE)## End(Not run)