Toward , this study chose a few classes during the Chengdu Shishi secondary school and you may Jinniu secondary school respectively, distributed three hundred questionnaires, retrieved 278 surveys, subtracted twelve invalid questionnaires and 266 appropriate surveys. The specialized analysis is actually complete away from .
Exploratory factor analysis (EFA) showed that the sports leisure attitude scale with 16 items was suitable for factor analysis (KMO = 0.87, Bartlett’s test for sphericity p < 0.001), and three common factors could be extracted, and the corresponding Cronbach' ? coefficients were 0.84, 0.81, and 0.83 respectively. In addition, the overall scale ? coefficient = 0.85; Confirmatory factor analysis (CFA) showed that the fitness indexes AGFI, CFI, NFI, and IFI were 0.92, 0.95, 0.93, and 0.91, which were all greater than the standard of 0.90, RMSEA = 0.03 (less than 0.05, with good adaptation); In addition, the combined reliability of the three common factors (potential variables) is more than 0.79, which shows that the scale has good reliability and validity.
Canonical correlation study is a mathematical means always sample the fresh correlation training between you to set of control parameters and another classification from criterion details
Exploratory factor analysis showed that the leisure motivation scale with 21 items was suitable for factor analysis (KMO = 0.78, Bartlett’s test for sphericity p < 0.001). The scale could extract 4 common factors, corresponding to Cronbach' ? coefficient is between 0.79–0.85, and the overall scale ? Coefficient = 0.88; Confirmatory factor analysis showed that the fitness indexes AGFI, CFI, NFI, and IFI were 0.91, 0.92, 0.92, and 0.93, which were all greater than the standard of 0.90, RMSEA = 0.04 (less than 0.05, good adaptation); In addition, the combined reliability of the four dimensions (potential variables) is more than 0.81, which shows that the reliability and validity of this scale are good.
Exploratory factor analysis showed that the leisure barriers scale with 17 items was suitable for factor analysis (KMO = 0.85, Bartlett ball test p < 0.001). The scale could extract three common factors, corresponding to Cronbach' ? coefficient is between 0.82–0.86, and the overall scale ? Coefficient = 0.85; Confirmatory factor analysis showed that the fitness indexes AGFI, CFI, NFI, and IFI were 0.94, 0.90, 0.91, and 0.93, which were all greater than the standard of 0.90, RMSEA = 0.02 (less than 0.05, good adaptation); In addition, the combined reliability of the three dimensions (potential variables) is more than 0.79, which shows that the reliability and validity of this scale are good.
Exploratory factor analysis showed that the leisure satisfaction scale with 25 items was suitable for factor analysis (KMO = 0.82, Bartlett’s test for sphericity p < 0.001). The scale could extract 6 common factors, corresponding to Cronbach' ? coefficient is between 0.81–0.86, and the overall scale ? Coefficient = 0.84; Confirmatory factor analysis showed that the fitness indexes AGFI, CFI, NFI, and IFI were 0.91, 0.93, 0.95, and 0.92 in order, which was all greater than the standard of 0.90, RMSEA = 0.03 (less than 0.05, good adaptation); In addition, the combined reliability of the six dimensions (potential variables) is more than 0.81, which shows that the reliability and validity of this scale are good.
Mathematical Analytics
It will find the maximum correlation between your linear consolidation out-of handle variables while the linear mixture of standard variables. Therefore, canonical correlation study tests brand new canonical correlation mixture of several requirement details and you may multiple manage parameters, Canonical correlation study can create a mixture of tall and unimportant canonical relationship. Essentially, it can supply the following the first guidance: you’re the average relationship coefficient normally reflect this new correlation education within linear blend of handle variables and the linear integration out-of basic variables. An average correlation coefficient have to arrive at a significant peak in order to depict the important correlation between the two categories of linear combinations. The second reason is the wisdom coefficient (i.e., the latest rectangular worth of normal relationship coefficient Roentgen). It means the normal activities of one’s practical adjustable can become explained of the normal activities of the handle adjustable (for around ten%). The third is the architectural coefficient (normal weight). It’s intended to control new correlation between your varying and new standards changeable on the respective normal linear combos. The absolute worth of the brand new coefficient need to be over 0.30 to spell it out that its particular regular linear combos have explanatory power.