# Computing confidence intervals for standardized regression coefficients.

@article{Jones2013ComputingCI, title={Computing confidence intervals for standardized regression coefficients.}, author={Jeff A. Jones and Niels G Waller}, journal={Psychological methods}, year={2013}, volume={18 4}, pages={ 435-53 } }

With fixed predictors, the standard method (Cohen, Cohen, West, & Aiken, 2003, p. 86; Harris, 2001, p. 80; Hays, 1994, p. 709) for computing confidence intervals (CIs) for standardized regression coefficients fails to account for the sampling variability of the criterion standard deviation. With random predictors, this method also fails to account for the sampling variability of the predictor standard deviations. Nevertheless, under some conditions the standard method will produce CIs with…

## 27 Citations

### A Comparative Investigation of Confidence Intervals for IndependentVariables in Linear Regression

- MathematicsMultivariate behavioral research
- 2016

The coverage probability of a large-sample confidence interval for the semipartial correlation coefficient derived from Aloe and Becker was highly accurate and robust in 98% of instances, and was better in small samples than the Yuan-Chan large- sample confidence intervals for a standardized regression coefficient.

### Simple and flexible Bayesian inferences for standardized regression coefficients

- Computer Science, MathematicsJournal of Applied Statistics
- 2019

Simulation studies show that Bayesian credible intervals constructed by the approaches have comparable and even better statistical properties than their frequentist counterparts, particularly in the presence of collinearity.

### Some Improvements in Confidence Intervals for Standardized Regression Coefficients

- MathematicsPsychometrika
- 2017

Yuan and Chan (Psychometrika 76:670–690, 2011. doi:10.1007/S11336-011-9224-6) derived consistent confidence intervals for standardized regression coefficients under fixed and random score…

### Some Improvements in Confidence Intervals for Standardized Regression Coefficients

- MathematicsPsychometrika
- 2017

Seven different heteroscedastic-consistent estimators were investigated in the current study as potentially better solutions for constructing confidence intervals on standardized regression coefficients under non-normality, and the HC5 estimator was more robust in a restricted set of conditions over the HC3 estimator.

### Standardized Regression Coefficients and Newly Proposed Estimators for [Formula: see text] in Multiply Imputed Data.

- MathematicsPsychometrika
- 2020

Simulations show that the proposed pooled standardized coefficient estimates are less biased than two earlier proposed pooled estimates, and that their 95% confidence intervals produce coverage close to the theoretical 95%.

### The Normal-Theory and Asymptotic Distribution-Free (ADF) Covariance Matrix of Standardized Regression Coefficients: Theoretical Extensions and Finite Sample Behavior

- MathematicsPsychometrika
- 2015

It is shown that the asymptotic distribution-free (ADF) method for computing the covariance matrix of standardized regression coefficients works well with nonnormal data in moderate-to-large samples using both simulated and real-data examples.

### The Normal-Theory and Asymptotic Distribution-Free (ADF) Covariance Matrix of Standardized Regression Coefficients: Theoretical Extensions and Finite Sample Behavior

- MathematicsPsychometrika
- 2013

Yuan and Chan (Psychometrika, 76, 670–690, 2011) recently showed how to compute the covariance matrix of standardized regression coefficients from covariances. In this paper, we describe a method for…

### Standardized Regression Coefficients and Newly Proposed Estimators for $${R}^{{2}}$$R2 in Multiply Imputed Data

- Mathematics
- 2020

Whenever statistical analyses are applied to multiply imputed datasets, specific formulas are needed to combine the results into one overall analysis, also called combination rules. In the context of…

### DIY bootstrapping: Getting the nonparametric bootstrap confidence interval in SPSS for any statistics or function of statistics (when this bootstrapping is appropriate).

- MathematicsBehavior research methods
- 2022

Researchers can generate bootstrap confidence intervals for some statistics in SPSS using the BOOTSTRAP command. However, this command can only be applied to selected procedures, and only to selected…

### On the Relationship Between Confidence Sets and Exchangeable Weights in Multiple Linear Regression

- MathematicsMultivariate behavioral research
- 2016

A general framework describing how CSs and the set of EWs for regression weights are estimated from the likelihood-based and Wald-type approach is introduced, and the analytical relationship betweenCSs and sets ofEWs is established.

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