Table 3. Results of hierarchical linear...

Table 3.

Results of hierarchical linear modelling – EI is dependent variable

Level and variables	Null Model	Model 1	Model 2	Model 3
Intercept	3.80 0 (0.07)	3.21 (0.06)	3.49 (0.07)	3.48 (0.06)
Class size		−0.01 (0.01) **	−0.01 (0.01)**	−0.01 (0.00)***
Class CGPA		0.01 (0.01)**	−0.01 (0.01)**	0.01 (0.01)**
Level 2
Age		0.01 (0.02)**	0.01 (0.01)**	0.01 (0.02)**
Gender		−0.02 (0.06)	−0.03 (0.08)	−0.03 (0.07)
EK			0.94 (0.04)**	0.52 (0.01)**
PDE			0.93 (0.03)**	0.41 (0.08)
PSE			0.02 (0.03)**	0.12 (0.01)**
PDE^*EK				0.09 (0.03)**
PSE^*EK				0.07 (0.03)**
Pseudo R²		0.20	0.63	0.12
σ²	0.71
τ₀₀	0.18
χ²	192.86***	121.99***	92.29***	183.47***

Level and variables	Null Model	Model 1	Model 2	Model 3
Intercept	3.80 0 (0.07)	3.21 (0.06)	3.49 (0.07)	3.48 (0.06)
Class size		−0.01 (0.01) **	−0.01 (0.01)**	−0.01 (0.00)***
Class CGPA		0.01 (0.01)**	−0.01 (0.01)**	0.01 (0.01)**
Level 2
Age		0.01 (0.02)**	0.01 (0.01)**	0.01 (0.02)**
Gender		−0.02 (0.06)	−0.03 (0.08)	−0.03 (0.07)
EK			0.94 (0.04)**	0.52 (0.01)**
PDE			0.93 (0.03)**	0.41 (0.08)
PSE			0.02 (0.03)**	0.12 (0.01)**
PDE^*EK				0.09 (0.03)**
PSE^*EK				0.07 (0.03)**
Pseudo R²		0.20	0.63	0.12
σ²	0.71
τ₀₀	0.18
χ²	192.86***	121.99***	92.29***	183.47***

Notes:

p-values are reported in parentheses (); σ² represents variance in individual level residuals; τ00 represents variance in organizational level residuals. Pseudo R² was calculated by using formula given by Kreft et al. (1998).

*p <0.10; **<0.05; ***p <0.01; Classes n = 4; students n = 200.

Age – Actual age of the respondent; gender, 1–male, 2–female; CGPA – actual CGPA obtained till last semester; entrepreneurship course studied 1–No, 2–Yes; doing own business, 1–No, 2–Yes; family doing business 1–No, 2–Yes

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