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. 2017 Jul 1;35(1):33–34.

Table 3. Multiple logistic regression showing associations between shape and other morphological features, according to Thomas and Kotze classification (n = 1160.

Shape Coef. Std. Err. 95% CI p value
Curved (base outcome)
Wavy
Constant -1.516 0.360 [-2.221; -0.811] <0.001**
Length 0.188 0.030 [0.129; 0.246] <0.001**
Direction (Forward)
     Straight -0.132 0.210 [-0.544; 0.280] 0.529
     Backward -0.937 0.203 [-1.335; -0.538] <0.001**
Unification (Absent)
     Divergent -0.601 0.231 [-1.054; -0.148] 0.009**
     Convergent -0.819 0.553 [-1.904; 0.265] 0.139
Straight
Constant 0.398 0.357 [-0.300; 1.097] 0.264
Length -0.485 0.031 [-0.108; 0.012] 0.114
Direction (Forward)
     Straight 0.023 0.230 [-0.427; 0.473] 0.920
     Backward -0.182 0.215 [-0.603; 0.239] 0.396
Unification (Absent)
     Divergent -0.286 0.215 [-0.707; 0.135] 0.183
     Convergent -0.226 0.465 [-1.137; 0.685] 0.626
LR Chi (2) (10) 115.87
Prob > Chi (2) <0.001**
Pseudo R2 0.0456

Notes. Coef. = regression coefficient; Std. Err. = standard error;

LR Chi (2)(x) refers to the Likelihood ratio Chi-square test statistic and associated degrees of freedom.

(Base): refers to the base outcome all other categories are compared to

*Statistically significant at p ≤ 0.05; **Statistically significant at p < 0.01