Model summary |
Model | R | R2 | Adjusted R2 | R2 change | F change | Sig. F change | Durbin-Watson | SE |
1 | 0.111 | 0.012 | 0.000 | 0.012 | 0.996 | 0.372 | - | 2.89 |
2 | 0.507 | 0.257 | 0.233 | 0.245 | 17.331 | 0.000 | 1.976 | 2.55 |
Predictive factor input |
Model | Predictors | (B) | (β) | Part C. | 95% CI | p-value | t-value |  |
1 | Constant | 2.475 |  |  | −0.12–5.07 | 0.061 | 1.88 |  |
Age | −0.022 | −0.86 | −0.088 | −0.06–0.02 | 0.274 | −1.10 |  |
Gender | 0.386 | 0.067 | 0.067 | −0.51–1.28 | 0.394 | 0.86 |  |
2 | Constant | 1.048 |  |  | −1.68–3.78 | 0.450 | 0.76 |  |
Age | 0.006 | 0.023 | 0.023 | −0.03–0.40 | 0.742 | 0.33 |  |
Gender | 0.237 | 0.041 | 0.041 | −0.55–1.02 | 0.550 | 0.60 |  |
Stroke DR | 0.067 | 0.403 | 0.390 | −0.04–0.09 | <0.00* | 5.70 |  |
Hosp. DR | 0.038 | 0.176 | 0.166 | 0.01–0.07 | 0.017* | 2.42 |  |
LEMF | −0.047 | −0.119 | −0.114 | −0.10–0.01 | 0.098 | −1.67 |  |
- a. Predictors: (constant), gender of the participants, age of the participants
- b. Predictors: (constant), gender, age (years), stroke duration (months), lower extremity motor function, duration of in-patient hospital stays (days) of the participants
- c. Dependent variable: ambulatory onset post-stroke
- General regression predictive equation: Y= a + bx
- Y = value of dependent variable; a = constant; b = regression coefficient of each predictor variable; x = value of each predictor variable
- Ambulatory onset post-stroke is therefore = 2.475 + bx
- Values of b and x will be added to the equation continuously depending on the number of predictor variables
- Model 1 is the first showing demographics (age and gender), model 2 is the second following model 1 and shows demographics (age and gender) and other independent (predictor) variables
- Key: Adjusted R2 Adjusted goodness-of-fit measure for the regression model, Part C. part correlation, SE Standard error, Hosp. Hospital, df degree of freedom, DR Duration, B unstandardized coefficient, β standardized coefficient, LEMF Lower extremity motor function
- *Significant at p ≤ 0.05; ANOVA summary: F = 10.918, df = 5, p < 0.001