BetaN {betaSandwich} | R Documentation |
Estimate Standardized Regression Coefficients and the Corresponding Sampling Covariance Matrix Assuming Multivariate Normality
Description
Estimate Standardized Regression Coefficients and the Corresponding Sampling Covariance Matrix Assuming Multivariate Normality
Usage
BetaN(object, alpha = c(0.05, 0.01, 0.001))
Arguments
object |
Object of class |
alpha |
Numeric vector.
Significance level |
Details
Note that while the calculation in BetaN()
is different from betaDelta::BetaDelta()
with type = "mvn"
,
the results are numerically equivalent.
BetaN()
assumes multivariate normality.
BetaHC()
is recommended in most situations.
Value
Returns an object
of class betasandwich
which is a list with the following elements:
- call
Function call.
- args
Function arguments.
- lm_process
Processed
lm
object.- gamma_n
Asymptotic covariance matrix of the sample covariance matrix assuming multivariate normality.
- gamma_hc
Asymptotic covariance matrix HC correction.
- gamma
Asymptotic covariance matrix of the sample covariance matrix.
- acov
Asymptotic covariance matrix of the standardized slopes.
- vcov
Sampling covariance matrix of the standardized slopes.
- est
Vector of standardized slopes.
Author(s)
Ivan Jacob Agaloos Pesigan
References
Dudgeon, P. (2017). Some improvements in confidence intervals for standardized regression coefficients. Psychometrika, 82(4), 928–951. doi:10.1007/s11336-017-9563-z
Pesigan, I. J. A., Sun, R. W., & Cheung, S. F. (2023). betaDelta and betaSandwich: Confidence intervals for standardized regression coefficients in R. Multivariate Behavioral Research. doi:10.1080/00273171.2023.2201277
See Also
Other Beta Sandwich Functions:
BetaADF()
,
BetaHC()
,
DiffBetaSandwich()
,
RSqBetaSandwich()
Examples
object <- lm(QUALITY ~ NARTIC + PCTGRT + PCTSUPP, data = nas1982)
std <- BetaN(object)
# Methods -------------------------------------------------------
print(std)
summary(std)
coef(std)
vcov(std)
confint(std, level = 0.95)