Correction: Bui (2024). How Debt and Attainment Relate through the GPA of Non-White College Students. Social Sciences 13: 407

Text Correction

There were three errors in the original publication (Bui 2024). In the “Methods” subsection, the term “linear” was misplaced; the term “parsimonious” was redundant; the phrase “bootstrap standard errors” lacked “ed” after “bootstrap.” Therefore, the phrase “a parsimonious linear multiple regression model and a linear logistic regression model” should be “a multiple linear regression model and a logistic regression model,” and the phrase “bootstrap standard error” should be “bootstrapped standard errors.”

A correction has been made to 3. Methodology, 3.3. Methods, Paragraph 1:

I employed the conditioning-based approach to answer the research questions (McBee 2022). With this approach, I constructed a multiple linear regression model and a logistic regression model. The first model addressed the effects of student loans on GPA, formalized as follows:

And 3. Methodology, 3.3. Methods, Paragraph 2:

The conditioning-based approach caused this indirect effect analysis to be distinctive from what Baron and Kenny (1986) suggested. The BCI method was used to assess indirect effects, and the analysis was conducted on Process (Version 3.5), an equation modeling tool developed by Hayes (2017). The BCI method employed resampling as the working principle. First, data were resampled 5000 times with replacement. Then, the mean of each indirect effect was estimated, and based on this estimation, the bootstrapped standard errors and the bootstrapped 95% CI (i.e., α = 0.05) were calculated. The output of these calculations consisted of the direct and indirect effects of loan status and debt levels on attainment and regression results, with regression statistics for both GPA and attainment as outcome variables. Employing the BCI method on Process helped address the issue of the nonnormal distribution of data points and minimized estimation bias, given that resampling moved the estimates to population parameters.

The author states that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.