Function to obtain the confidence interval for a standardized regression coefficient.
ci.src(beta.k = NULL, SE.beta.k = NULL, N = NULL, K = NULL, R2.Y_X = NULL,
R2.k_X.without.k = NULL, conf.level = 0.95, R2.Y_X.without.k = NULL,
t.value = NULL, b.k = NULL, SE.b.k = NULL, s.Y = NULL, s.X = NULL,
alpha.lower = NULL, alpha.upper = NULL, Suppress.Statement = FALSE, ...)
the standardized regression coefficient
the standard error of the standarized regression coefficient
sample size
the number of predictors
the squared multiple correlation coefficient predicting Y from the k predictor variables
the squared multiple correlation coefficient predicting the kth predictor variable (i.e., the predictor of interest) from the remaining p-1 predictor variables
desired level of confidence for the computed interval (i.e., 1 - the Type I error rate)
the squared multiple correlation coefficient predicting Y from the p-1 predictor variable with the kth predictor of interest excluded
the t-value evaluating the null hypothesis that the population regression coefficient for the kth predictor equals zero
the unstandardized regression coefficient
the standard error of the unstandardized regression coefficient
standard deviation of Y, the dependent variable
standard deviation of X, the predictor variable of interest
the Type I error rate for the lower confidence interval limit
the Type I error rate for the upper confidence interval limit
TRUE
or FALSE
statement specifying whether or not a statement should be printed
that identifies the type of confidence interval formed
optional additional specifications for nested functions
Returns the confidence limits specified for the regression coefficient of interest from the standard approach to confidence interval formation or from the noncentral approach to confidence interval formation using the noncentral t-distribution.
For standardized variables, do not specify the standard deviation of the variables and input the
standardized regression coefficient for b.k
.
Kelley, K. (2007). Constructing confidence intervals for standardized effect sizes: Theory, application, and implementation. Journal of Statistical Software, 20 (8), 1--24.
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.
Kelley, K., & Maxwell, S. E. (2008). Sample Size Planning with applications to multiple regression: Power and accuracy for omnibus and targeted effects. In P. Alasuuta, J. Brannen, & L. Bickman (Eds.), The Sage handbook of social research methods (pp. 166--192). Newbury Park, CA: Sage.
Smithson, M. (2003). Confidence intervals. New York, NY: Sage Publications.
Steiger, J. H. (2004). Beyond the F Test: Effect size confidence intervals and tests of close fit in the Analysis of Variance and Contrast Analysis. Psychological Methods, 9, 164--182.
ss.aipe.reg.coef
, conf.limits.nct
, ci.reg.coef
, ci.rc