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Table 7 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 Nat Phy Stat
Intercept − 3.26* (0.56) − 1.83* (0.69) 0.60 (1.42)
Gender (female)    
Male − 1.56* (0.55) − 0.59 (0.74) − 2.04 (1.63)
CU male 0.04* (0.01) − 0.06 (0.04) − 0.11 (0.14)
CU female 0.00 (0.01) − 0.12* (0.05) − 0.15 (0.16)
HSdiploma (other “liceo”)    
Scientific − 0.02 (0.20) 0.07 (0.31) − 0.79 (0.60)
Classical 0.06 (0.25) − 0.09 (0.35) − 0.55 (0.75)
Technical − 0.22 (0.25) − 1.24* (0.61) − 0.73 (0.61)
Vocational − 0.04 (0.37) − 0.62 (0.89) − 0.38 (1.24)
Abroad/other − 0.64 (0.65) 0.07 (1.09) 2.11 (1.34)
Age (≤19)    
>19 − 0.39* (0.13) − 0.68* (0.2) − 0.86* (0.27)
Macro-region (Islands)    
North 0.40* (0.18) 0.64* (0.27) − 1.02 (0.65)
Center 0.19 (0.19) 0.23 (0.28) − 1.32 (0.69)
South − 0.13 (0.20) 0.01 (0.30) − 2.51* (0.73)
HS final mark (60) 0.03* (0.01) 0.01* (0.01) 0.01 (0.01)
HSdiploma x Gender (female)    
Scientific 0.46 (0.44) − 0.32 (0.61) 1.83 (1.10)
Classical 1.05* (0.53) 0.39 (0.67) 1.24 (1.30)
Technical 0.39 (0.47) 0.48 (0.82) 0.77 (1.12)
Vocational 0.15 (0.62) 0.50 (1.12) 0.91 (1.67)
Abroad/other 0.90 (0.93) 0.16 (1.47) 23.02 (598.91)
  1. Baselines are in brackets. Cohort of freshmen enrolled in 2014. Natural Sciences, physics and statistics. The asterisk indicates a corresponding p-value <0.05. Standard errors are in brackets