Construction and validation of a risk prediction model for depressive symptoms in a middle-aged and elderly arthritis population

Figure 1 Least absolute shrinkage and selection regression model. A: The least absolute shrinkage and selection regression model uses log(lambda) sequences with nonzero coefficients produced by the optimal lambda to create coefficient distributions for the selection of clinical and demographic characteristics; B: The log(lambda) sequence was used to generate the coefficient distribution, and vertical lines were created at the values determined by 10-fold cross-validation. Lambda.1-se was chosen as the ideal lambda in this study, resulting in 16 features with non-zero coefficients.