Table 2.
Explains the practical significance of each variable on the duration of benefit.
| Tests of between-subjects effects |
||||||
|---|---|---|---|---|---|---|
| Dependent variable: month of benefit |
||||||
| Source | Type III sum of squares | df | Mean square | F | Sig. | Partial eta squared |
| Corrected model | 2477.648a | 5 | 495.530 | 48.066 | .000 | .710 |
| Intercept | 154.738 | 1 | 154.738 | 15.010 | .000 | .133 |
| Age | 5.280 | 1 | 5.280 | .512 | .476 | .005 |
| BMI | 3.460 | 1 | 3.460 | .336 | .564 | .003 |
| MF atrophy | 1323.191 | 1 | 1323.191 | 128.349 | .000 | .567 |
| sex | 24.014 | 1 | 24.014 | 2.329 | .130 | .023 |
| MF atrophy × sex | 10.914 | 1 | 10.914 | 1.059 | .306 | .011 |
| Error | 1010.313 | 98 | 10.309 | |||
| Total | 16028.000 | 104 | ||||
| Corrected total | 3487.962 | 103 | ||||
R2 = .710 (adjusted R2 = .696). Larger values of partial (η2 = eta squared) indicate a greater amount of variation accounted for by the model term, to a maximum of 1. Here the individual term (degree of LMF atrophy) is statistically significant and has great effect on the value of months of benefit.
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