A function used to plan sample size from the accuracy in parameter estimation approach for a regression coefficient of interest given the input specification.
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)
Returns the necessary sample size in order for the goals of accuracy in parameter estimation to be satisfied for the confidence interval for a particular regression coefficient given the input specifications.
Population value of the squared multiple correlation coefficient
Population value of the squared multiple correlation coefficient predicting the jth predictor variable from the remaining p-1 predictor variables
the number of predictor variables
the regression coefficient for the jth predictor variable (i.e., the predictor of interest)
the desired width of the confidence interval
which width ("Full"
, "Lower"
, or "Upper"
) the width refers
to (at present, only "Full"
can be specified)
the population standard deviation of Y (i.e., the dependent variables)
the population standard deviation of the jth X variable (i.e., the predictor variable of interest)
Population correlation matrix for the p
predictor variables
Population p
length vector of correlation between the dependent variable (Y) and the p
independent variables
identifies which of the p
predictors is of interest
specify with a TRUE
or FALSE
statement whether or not the noncentral approach to sample size planning should be used
Type I error rate for the lower confidence interval limit
Type I error rate for the upper confidence interval limit
desired level of confidence for the computed interval (i.e., 1 - the Type I error rate)
degree of certainty that the obtained confidence interval will be sufficiently narrow
an alias for degree.of.certainty
an alias for degree.of.certainty
TRUE
/FALSE
statement whether or not a sentence describing the situation defined is printed with the necessary sample size
Ken Kelley (University of Notre Dame; KKelley@ND.Edu)
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.
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.
ss.aipe.reg.coef.sensitivity
, conf.limits.nct