Hierarchical regression model
From the results of the hierarchical regression analysis (see Table 9),
it can be seen that the two independent variables of
”depression-anxiety-stress” and ”general health” in Model 1 can explain
24.8% of the variance of the dependent variable of family life quality.
The F value is 45.060 (p<0.000), reaching a significant level
of 0.05. It shows that the regression coefficients of the two predictors
of ”depression-anxiety-stress” and ”general health” are both
significant, and the standardized regression coefficient β values of
these two independent variables are -0.426 (p<0.000) and 0.438
(p<0.000), respectively, both reached a significant level.
Among them, the influence of depression-anxiety-stress on the family
life quality is negative, and the influence of general health on the
family life quality is positive. If the two independent variables of
web-based learning tools and self-efficacy are further invested, the
overall explanatory variation increases by 15.7%
(△R2), and the F value of the significant change is
equal to 35.877 (p<0.000), which means web-based learning
tools and self-efficacy have significant effects on the quality of
family life. The F-value of the stratified binary linear regression
overall tests was 46.205 (p<0.000), reaching a significant
level of 0.05. It represents that the four predictors have significant
explanatory power for family life quality, and their common explanatory
variation is 40.5%.
Table 9 Hierarchical linear regression results