Fig 1.
The flow chart summarizing the predictor variable choice for Model I and Model II.
Table 1.
Patient demographics.
Fig 2.
The Chi-squared regression coefficients with p values for the predictors in the Model I (logistic regression model).
Femoral fixation was the most important and MCV the least important predictor in this model. MCV = Mean corpuscular volume, CCI = Carlson Comorbidity Index, ASA score = American Society of Anesthesiologists score, BMI = Body mass index.
Fig 3.
The calibration curve for the Model I (logistic regression model).
On the x-axis are the predicted probabilities and on the y-axis the observed probabilities. A perfectly calibrated model would follow the straight dashed line referred as “ideal” in the picture. On average, the Model I overestimated the probability of revision for dislocation in patients that had low probability of this outcome, and underestimated the probability of revision for dislocation in patients that had the highest probability of this outcome.
Fig 4.
The calibration curve for the Model II (elastic net).
On the x-axis are the predicted probabilities and on the y-axis are the observed probabilities. The predicted probability (black curve) moves farther from the true probability (red line) as the predicted value increases, indicating that the model underestimates the probability of dislocation for the patients having the highest probability of this outcome.
Fig 5.
The prediction density graph for the Model II (elastic net).
This graph presents how well the model discriminates the patients revised for dislocation (blue) from patients not revised for dislocation (red). In an ideal model the blue and red parts would be completely separated.