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3.4 Statistical analyses
In order to test our hypotheses, we performed a regression analysis using
SES as an independent variable and all the variables measuring students’
participation in the wider community, participation in school, and discus-
sion serving as dependent variables.
For this, we used the software RALSA. Ralsa is an R analyzer that was
developed specifically for large-scale assessments with large and complex
sampling procedures (Mirazchiyski, 2021).
4. Results
4.1 Participation in the wider community
First, examine the relationship between SES and students’ participation in
the community (out of school) for students in Slovenia, Croatia, and Italy.
Table 18: Relationship between participation out of school (S_SCHPART) and SES
Coefficients t_value
0,85 (0,22) 3,92
Slovenia
Croatia 0,07 (0,25) 0,30
Italy 0,79 (0,19) 4,20
*Standard errors appear in parentheses.
The Table 18 shows the results of the regression analysis. In Slovenia,
the coefficient is 0.85, indicating a positive relationship between participa-
tion in the community and SES. The t-value of 3.92 shows that the relation-
ship is statistically significant. This means that students who had a higher
SES tend to participate more in civic activities outside of school. In Croatia,
no statistically significant relationship was found. In Italy, the coefficient is
0.79, indicating a positive relationship between participation out of school
and SES. The t-value of 4.20 shows that the relationship is statistically sig-
nificant. Overall, the results suggest that there is a positive relationship be-
tween ICCS students’ participation out of school and SES in Slovenia and
Italy, but not in Croatia.
In Table 19, the results of regression analysis to test the relationship be-
tween type of participation in the community (S_COMPART) and SES are
shown.
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3.4 Statistical analyses
In order to test our hypotheses, we performed a regression analysis using
SES as an independent variable and all the variables measuring students’
participation in the wider community, participation in school, and discus-
sion serving as dependent variables.
For this, we used the software RALSA. Ralsa is an R analyzer that was
developed specifically for large-scale assessments with large and complex
sampling procedures (Mirazchiyski, 2021).
4. Results
4.1 Participation in the wider community
First, examine the relationship between SES and students’ participation in
the community (out of school) for students in Slovenia, Croatia, and Italy.
Table 18: Relationship between participation out of school (S_SCHPART) and SES
Coefficients t_value
0,85 (0,22) 3,92
Slovenia
Croatia 0,07 (0,25) 0,30
Italy 0,79 (0,19) 4,20
*Standard errors appear in parentheses.
The Table 18 shows the results of the regression analysis. In Slovenia,
the coefficient is 0.85, indicating a positive relationship between participa-
tion in the community and SES. The t-value of 3.92 shows that the relation-
ship is statistically significant. This means that students who had a higher
SES tend to participate more in civic activities outside of school. In Croatia,
no statistically significant relationship was found. In Italy, the coefficient is
0.79, indicating a positive relationship between participation out of school
and SES. The t-value of 4.20 shows that the relationship is statistically sig-
nificant. Overall, the results suggest that there is a positive relationship be-
tween ICCS students’ participation out of school and SES in Slovenia and
Italy, but not in Croatia.
In Table 19, the results of regression analysis to test the relationship be-
tween type of participation in the community (S_COMPART) and SES are
shown.
206
