Closed aminadibi closed 7 years ago
One could also model Percent Predicted FEV1, which would not require height and weight coefficients:
Baseline Percent Predicted FEV1 | |||||||
---|---|---|---|---|---|---|---|
Effect | Estimate | Standard Error | DF | t Value | Pr > | t | |
Intercept | 865.8 | 9.108 | 5588 | 95.06 | <.0001 | ||
age_baseline | -2.5 | 0.168 | 2.40E+04 | -14.91 | <.0001 | ||
gender | 34.17 | 2.362 | 2.40E+04 | 14.46 | <.0001 | ||
smoker | -57.88 | 3.277 | 2.40E+04 | -17.66 | <.0001 |
Percent Predicted FEV1 Decline | |||||||
---|---|---|---|---|---|---|---|
Effect | Estimate | Standard Error | DF | t Value | Pr > | t | |
Intercept | 21.13 | 0.432 | 5589 | 48.92 | <.0001 | ||
age_baseline | -0.07 | 7.69E-03 | 2.40E+04 | -9.35 | <.0001 | ||
gender | 0.802 | 0.107 | 2.40E+04 | 7.47 | <.0001 | ||
Smoker | -3.8 | 0.142 | 2.40E+04 | -26.8 | <.0001 | ||
yearYear | -1.83 | 0.014 | 2.40E+04 | -130.91 | <.0001 |
with model fit statistics as follows:
Fit Statistics | |
---|---|
-2 Res Log Likelihood | -123232 |
AIC (smaller is better) | -123226 |
AICC (smaller is better) | -123226 |
BIC (smaller is better) | -123206 |
Null Model Likelihood Ratio Test | ||
---|---|---|
DF | Chi-Square | Pr > ChiSq |
2 | 52973.77 | <.0001 |
Modified Zafar's CMAJ Regression (removing O'Connor's slope) yields these new coefficients:
Model fit statistics are: