Partially standardized coefficients

noetsi

Fortran must die
#1
This is for multilevel models. I don't understand what they are saying here exactly. What are partially standardized coefficients? And how do you calculate them?

Instead, the standardized coefficients can be used (Ferron et al. 2008; Snijders and Bosker 2012). These can be obtained by standardizing (i.e. M = 0; SD = 1) each variable before analysis (Ferron et al. 2008) or by standardizing each regression coefficient by multiplying it by the standard deviation of X and dividing by the standard deviation of Y (Snijders and Bosker 2012).

For the example analysis, Eq. 2 was estimated, and the standardized coefficient for Female is 0.004 (p > 0.05); for Internet is 0.186 (p < 0.05) and for Confidence is 0.262 (p < 0.05). This indicates that the coefficient for Female is not significantly different from zero; that one standard deviation increase in the Internet variable is related to 0.186 expected standard deviations increase in math achievement; and that one standard deviation increase in the Confidence variable is related to 0.262 expected standard deviations increase in math achievement, controlling for associated covariates.

Although these measures are now comparable, the interpretation for binary covariates, such as Female, may still be somewhat difficult; instead, the researcher can dummy code the binary covariate and standardize the outcome variable resulting in partially standardized coefficients. For the example analysis, this results in a coefficient of 0.008 (p > 0.05) for Female and 0.45 (p < 0.05) for Internet indicating that females are not significantly different from males on math achievement, when controlling for associated measures, and that students with internet connection are expected on average to score 0.45 standard deviations higher on math achievement, controlling for associated measures.
I don't understand what dummy code the the binary covariate means. They are already dummy variables.

https://largescaleassessmentsineducation.springeropen.com/articles/10.1186/s40536-018-0061-2