Practical Business Statistics 2022
DOI: 10.1016/b978-0-12-820025-4.00012-9
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Multiple Regression

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Cited by 21 publications
(5 citation statements)
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“…To eliminate the undesired impact of extreme values on the analysis results, all continuous variables are under winsorization at 1%. Figure 1a presents an overview of the collected sample from the standpoint of firm size (SIZE), where this study employs the natural logarithm of total assets to assess firm size, in line with the previous literature [30,35]. Figure 1b demonstrates the level of financial performance (ROE) of the sample firms, which serves as a useful indicator to gauge the earnings efficiency of firms utilizing their capital.…”
Section: Sample and Datamentioning
confidence: 80%
“…To eliminate the undesired impact of extreme values on the analysis results, all continuous variables are under winsorization at 1%. Figure 1a presents an overview of the collected sample from the standpoint of firm size (SIZE), where this study employs the natural logarithm of total assets to assess firm size, in line with the previous literature [30,35]. Figure 1b demonstrates the level of financial performance (ROE) of the sample firms, which serves as a useful indicator to gauge the earnings efficiency of firms utilizing their capital.…”
Section: Sample and Datamentioning
confidence: 80%
“…There were no significant differences between respondents and nonrespondents on parent age, sex, ethnicity, education level, or income. To allow for more direct comparisons between regression coefficients, all study variables were standardized before analyses (Siegel & Wagner, 2022) by subtracting the mean of the original variable from the raw value and then dividing it by the standard deviation of the original variable (i.e., z -score standardization). Because each scale is measured in different units, it is not possible to make direct comparisons between unstandardized regression coefficients in a model (Siegel & Wagner, 2022).…”
Section: Methodsmentioning
confidence: 99%
“…To allow for more direct comparisons between regression coefficients, all study variables were standardized before analyses (Siegel & Wagner, 2022) by subtracting the mean of the original variable from the raw value and then dividing it by the standard deviation of the original variable (i.e., z -score standardization). Because each scale is measured in different units, it is not possible to make direct comparisons between unstandardized regression coefficients in a model (Siegel & Wagner, 2022). Standardizing the variables before conducting a linear regression will address this problem by expressing the coefficients in terms of standard deviation.…”
Section: Methodsmentioning
confidence: 99%
“…Sex and motion (average frame‐wise displacement) were included as covariates in all analyses. Standardized beta coefficients were generated for reporting, as these provide an interpretable and generalizable measure of effect size, reflecting the number of standard deviations of the predictor variable associated with one standard deviation of change in the outcome variable (Siegel & Wagner, 2022).…”
Section: Methodsmentioning
confidence: 99%