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Table 5 OLS regression model of weekly tutoring time of youth during summer and winter holidays (N = 2313)

From: Children born in July and August: a study on the age regulation in primary school and student’s education access and development

Independent variables Unstandardized regression coefficient SE of B Sig.
(Constant) 3.391*** .693 .000
Male −.233 .127 .066
Birth month −.923 .531 .083
Birth month2 .221 .128 .085
School type4 −.001 .001 .227
Male × school type4 × birth month .003* .001 .021
Male × school type 4 × birth month2 −.001* .000 .017
Family monthly income(yuan) −.120 .074 .104
Grade −.889* .393 .024
Grade2 .115 .066 .083
Grade × family monthly income .198*** .061 .001
Grade2 × family monthly income −.034*** .010 .001
Temperament—active learner .201*** .063 .001
Temperament—extroverted .182** .070 .010
Temperament—self-disciplined −.314*** .062 .000
Only child .174 .091 .056
R 2 .070
Adjusted R 2 .064
Significance level of model .000
  1. Note: (i)Tutoring time is obtained from the question “Average tutoring time during summer and winter holidays”; data is subsequently standardized. Temperament factor is obtained through scale of attitude and behavior; (ii) based on Chinese high school education resource allocation, we investigated different schools of the surveyed teenagers. We categorized education resource allocation as 1 = key class of key school; 2 = ordinary class of key school; 3 = key class of ordinary school; 4 = ordinary class of ordinary school. Now, the school type is no longer a fixed nominal level variable but an ordinal level variable. Thus, we could conduct data conversion and regression
  2. *P < 0.05, **P < 0.01, ***P < 0.001