dot-sehatslopeshatprimetb: Standard Errors of Standardized Estimates of Regression...
In jeksterslabds/jeksterslabRlinreg: Jekster's Lab Linear Regression Utilities

Description Usage Arguments Details Author(s) References See Also

Standard Errors of Standardized Estimates of Regression Coefficients (Textbook)

.sehatslopeshatprimetb(
  slopeshat = NULL,
  sehatslopeshat = NULL,
  slopeshatprime = NULL,
  X,
  y
)

`slopeshat`	Numeric vector of length `p` or `p` by `1` matrix. p \times 1 column vector of estimated regression slopes ≤ft( \boldsymbol{\hat{β}}_{2, 3, \cdots, k} = ≤ft\{ \hat{β}_2, \hat{β}_3, \cdots, \hat{β}_k \right\}^{T} \right) .
`sehatslopeshat`	Numeric vector of length `p` or `p` by `1` matrix. p \times 1 column vector of estimated standard errors of estimates of regression slopes ≤ft( \mathbf{\widehat{se}}_{\boldsymbol{\hat{β}}_{2, 3, \cdots, k}^{\prime}} = ≤ft\{ \mathrm{\hat{se}}_{\hat{β}_{2}^{\prime}}, \mathrm{\hat{se}}_{\hat{β}_{3}^{\prime}}, \cdots, \mathrm{\hat{se}}_{\hat{β}_{k}^{\prime}} \right\}^{T} \right) .
`slopeshatprime`	Numeric vector of length `p` or `p` by `1` matrix. p \times 1 column vector of estimated standardized regression slopes ≤ft( \boldsymbol{\hat{β}}_{2, 3, \cdots, k} = ≤ft\{ \hat{β}_2, \hat{β}_3, \cdots, \hat{β}_k \right\}^{T} \right) .
`X`	`n` by `k` numeric matrix. The data matrix \mathbf{X} (also known as design matrix, model matrix or regressor matrix) is an n \times k matrix of n observations of k regressors, which includes a regressor whose value is 1 for each observation on the first column.
`y`	Numeric vector of length `n` or `n` by `1` matrix. The vector \mathbf{y} is an n \times 1 vector of observations on the regressand variable.

\mathbf{\widehat{se}}_{\boldsymbol{\hat{β}}_{2, \cdots, k}^{\prime}} = \mathbf{\widehat{se}}_{\boldsymbol{\hat{β}}_{2, \cdots, k}} \frac{\boldsymbol{\hat{β}}_{2, \cdots, k}^{\prime}}{\boldsymbol{\hat{β}}_{2, \cdots, k}}

According to Yuan and Chan (2011), this standard error is biased.

Ivan Jacob Agaloos Pesigan

Yuan, K., Chan, W. (2011). Biases and Standard Errors of Standardized Regression Coefficients. Psychometrika 76, 670-690. doi:10.1007/s11336-011-9224-6.

Other standard errors of estimates of regression coefficients functions: .sehatbetahatbiased(), .sehatbetahat(), .sehatslopeshatprimedelta(), sehatbetahatbiased(), sehatbetahat(), sehatslopeshatprimedelta(), sehatslopeshatprimetb()