ss.aipe.reg.coef.sensitivity: Sensitivity analysis for sample size planning from the Accuracy in Parameter Estimation Perspective for the (standardized and unstandardized) regression coefficient

Description

Performs a sensitivity analysis when planning sample size from the Accuracy in Parameter Estimation Perspective for the standardized or unstandardized regression coefficient.

Usage

ss.aipe.reg.coef.sensitivity(True.Var.Y = NULL, True.Cov.YX = NULL,
True.Cov.XX = NULL, Estimated.Var.Y = NULL, Estimated.Cov.YX = NULL,
Estimated.Cov.XX = NULL, Specified.N = NULL, which.predictor = 1, 
w = NULL, Noncentral = FALSE, Standardize = FALSE, conf.level = 0.95, 
degree.of.certainty = NULL, assurance=NULL, certainty=NULL,
 G = 1000, print.iter = TRUE)

Value

Results: a matrix containing the empirical results from each of the G replications of the simulation
Specifications: a list of the input specifications and the required sample size
Summary.of.Results: summary values for the results of the sensitivity analysis (simulation study) given the input specification

Arguments

True.Var.Y: Population variance of the dependent variable (Y)
True.Cov.YX: Population covariances vector between the p predictor variables and the dependent variable (Y)
True.Cov.XX: Population covariance matrix of the p predictor variables
Estimated.Var.Y: Estimated variance of the dependent variable (Y)
Estimated.Cov.YX: Estimated covariances vector between the p predictor variables and the dependent variable (Y)
Estimated.Cov.XX: Estimated Population covariance matrix of the p predictor variables
Specified.N: Directly specified sample size (instead of using Estimated.Rho.YX and Estimated.RHO.XX)
which.predictor: identifies which of the p predictors is of interest
w: desired confidence interval width for the regression coefficient of interest
Noncentral: specify with a TRUE or FALSE statement whether or not the noncentral approach to sample size planning should be used
Standardize: specify with a TRUE or FALSE statement whether or not the regression coefficient will be standardized
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
G: the number of generations/replication of the simulation student within the function
print.iter: specify with a TRUE/FALSE statement if the iteration number should be printed as the simulation within the function runts

Author

Ken Kelley (University of Notre Dame; KKelley@ND.Edu)

Details

Direct specification of True.Rho.YX and True.RHO.XX is necessary, even if one is interested in a single regression coefficient, so that the covariance/correlation structure can be specified when the simulation student within the function runs.

References

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