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Table 2 Description of the different variables

From: Multiple imputation using chained equations for missing data in TIMSS: a case study

Variable Type of variable Description
Age Continuous  
Number of books (Books) Ordinal Five categories:
1 Less than one shelf
2 One shelf
3 One bookcase
4 Two bookcases
5 Three or more bookcases
Possessing calculator (Calculator) Binary Two categories:
1 Yes
0 Otherwise
Possessing computer (Computer) Binary Two categories:
1 Yes
0 Otherwise
Possessing study desk (Desk) Binary Two categories:
1 Yes
0 Otherwise
Possessing a dictionary (Dictionary) Binary Two categories:
1 Yes
0 Otherwise
Possessing internet connection (Internet_connection) Binary 2 Two categories:
1 Yes
0 Otherwise
Parents’ highest education level (Parents’_highest_ed_level) Ordinal Five categories:
1 University degree
2 Completed postsecondary but not university
3 Completed upper-secondary education
4 Completed lower-secondary education
5 Less than lower-secondary education
Parents born in country (Parents_born_country) Nominal Three categories:
1 Both parents born in country
2 Only one parent born in country
3 Neither parent born in country
Gender of student (Female) Binary Two categories:
1 Female
0 Male
Spend time work on paid jobs (Work_paid_job) Ordinal Five categories:
1 No time
2 Less than one hour
3 One to two hours
4 More than two hours but less than four/
5 Four or more hours
Index of availability of mathematics resources (Index_math_ress) Ordinal Three categories:
1 High
2 Medium
3 Low
First plausible value in mathematics (BSMMAT01) Continuous  
First plausible value in science (BSSSCI01) Continuous