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Journal of Population Sciences

Table 5 Parameter estimates θ’s of the segmented regression models by degree course

From: An analysis of Italian university students’ performance through segmented regression models: gender differences in STEM courses

Variable

Bio

Biot

Chem

Intercept

− 1.06* (0.35)

0.71 (0.46)

− 3.63* (0.62)

Gender (female)

   

Male

− 0.59 (0.45)

− 0.85 (0.58)

0.00 (0.67)

CU male

0.00 (0.02)

0.04* (0.01)

0.01 (0.02)

CU female

− 0.02 (0.02)

0.02 (0.01)

− 0.03 (0.02)

HSdiploma (other “liceo”)

   

Scientific

− 0.10 (0.11)

− 0.68* (0.18)

− 0.10 (0.29)

Classical

− 0.14 (0.13)

− 0.56* (0.2)

− 0.10 (0.32)

Technical

− 0.35* (0.18)

− 0.72* (0.3)

− 0.36 (0.35)

Vocational

− 0.51* (0.23)

− 0.32 (0.39)

− 0.85 (0.68)

Abroad/other

− 0.57 (0.46)

− 0.29 (0.54)

− 3.13* (1.19)

Age (≤19)

   

> 19

− 0.41* (0.10)

− 0.30 (0.16)

− 0.74* (0.17)

Macro-region (Islands)

   

North

0.36* (0.11)

− 0.23 (0.20)

0.17 (0.20)

Center

0.20 (0.11)

− 0.17 (0.20)

0.09 (0.21)

South

− 0.25* (0.11)

− 0.07 (0.20)

− 0.64* (0.24)

HS final mark (60)

0.01 (0.00)

− 0.01* (0.00)

0.03* (0.01)

HSdiploma x Gender (female)

   

Scientific

− 0.14 (0.36)

− 0.24 (0.44)

− 0.40 (0.63)

Classical

− 0.29 (0.41)

− 0.45 (0.49)

− 1.14 (0.72)

Technical

0.30 (0.42)

− 0.20 (0.53)

− 0.65 (0.67)

Vocational

0.45 (0.48)

− 0.54 (0.70)

− 0.21 (0.94)

Abroad/other

0.51 (0.99)

− 0.24 (1.18)

2.66 (1.44)

  1. Baselines are in brackets. Cohort of freshmen enrolled in 2014. Biology, biotechnology and chemistry. The asterisk indicates a corresponding p-value <0.05. Standard errors are in brackets