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Journal of Population Sciences

Table 6 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

Comp

Eng

Math

Intercept

− 1.97 (1.05)

− 2.78* (0.23)

− 3.24* (0.79)

Gender (female)

   

Male

− 4.32* (1.09)

− 0.75* (0.30)

− 0.64 (0.95)

CU male

0.01 (0.02)

− 0.04* (0.01)

− 0.07 (0.05)

CU female

− 0.78* (0.39)

− 0.02 (0.01)

− 0.17* (0.05)

HSdiploma (other “liceo”)

   

Scientific

− 0.67 (0.39)

− 0.01 (0.13)

0.36 (0.30)

Classical

− 0.64 (0.54)

− 0.09 (0.14)

0.51 (0.37)

Technical

− 1.13* (0.4)

− 0.30 (0.16)

− 0.06 (0.44)

Vocational

− 1.36 (0.75)

− 1.06* (0.53)

− 0.61 (1.01)

Abroad/other

0.89 (1.50)

− 0.13 (0.36)

− 24.93 (573.89)

Age (≤19)

   

>19

− 0.49* (0.11)

− 0.58* (0.06)

− 1.32* (0.33)

Macro-region (Islands)

   

North

1.40* (0.21)

0.10 (0.06)

0.55 (0.30)

Center

0.93* (0.23)

− 0.07 (0.07)

0.56 (0.31)

South

0.34 (0.22)

− 0.19* (0.07)

− 0.02 (0.32)

HS final mark (60)

0.02* (0.00)

0.02* (0.00)

0.04* (0.01)

HSdiploma x Gender (female)

   

Scientific

1.75* (0.60)

0.33 (0.24)

− 0.79 (0.84)

Classical

2.17* (0.78)

0.42 (0.26)

0.17 (0.95)

Technical

1.92* (0.60)

0.53* (0.25)

− 0.04 (0.93)

Vocational

1.90* (0.92)

1.18* (0.58)

0.46 (1.64)

Abroad/other

− 0.38 (1.63)

0.32 (0.45)

1.58 (847.23)

  1. Baselines are in brackets. Cohort of freshmen enrolled in 2014. Computer Science, engineering and mathematics. The asterisk indicates a corresponding p-value <0.05. Standard errors are in brackets