Multiple regression model
Based on data analysis, the study uses multiple linear regression
equations to determine the quantitative correlation between multiple
independent variables and dependent variables (see Table 8). All
independent variables have significant predictive power for dependent
variables. In the statistical data onto collinearity of all independent
variables, the VIF value is less than 10 means that there is no
collinearity between the respective variables, and the regression
equation of the model is stable and reliable. The residual values of
[-2, +2] can explain most of the predicted values and prove the
validity of the regression equation. Among the four predictors, four
variables have significant predictive power for family quality of life,
followed by self-efficacy, web-based learning tools,
depression-anxiety-stress and general health. The multiple correlation
coefficient between the four predictors and the dependent variable
family quality of life is 0.636, the coefficient of determination
(R2) is 0.405, and the F value of the regression model
integrity test is 46.205 (p=0.000<0.05), so the four
predictions The variables can effectively explain 40.5% of the
variation to family quality of life.
From the perspective of the predictive power of each variable, the most
predictive factor of family quality of life is the self-efficacy
independent variable, with an explanatory variation of 29%; followed by
the web-based learning tool, which explains the variation 34.9%; the
predictive power of the remaining two independent variables
depression-anxiety-stress and general health are 37.0% and 40.5%
respectively. From the perspective of standardized regression
coefficients, the β values of the four predictors in the regression
model are 0.336, 0.209, -0.247, 0.222, where a positive number means
that its influence on family quality of life is positive, and a negative
number mean its It has a negative impact on family quality of life.
The non-standardized regression equation is as follows: family life
quality = 7.577 + 0.783 * self-efficacy + 0.329 * web-based learning
tools-0.346 * (depression-anxiety-stress) + 0.747 * general health
The standardized regression equation is as follows: family quality of
life=0.336*self-efficacy+0.209*web-based learning
tool-0.247*(depression-anxiety-stress) + 0.222* general health
Table 8 Results of multiple regression analysis