List of abbreviations List of tables
List of figures Acknowledgements
1. INTRODUCTION General Objective
2. RESEARCH QUESTIONS
3. DATA
3.1 Participants
3.2 Data colection
3.3 Description of the database
3.4 Variables
3.5 Descriptive Statistics
4. ANALYSES TECHNIQUES
4.1 Multiple Corresponden ce Analysis
4.2 Cluster Analysis and Contingency Tables
4.3 Multiple Discriminant Analysis
4.4 MANOVA
4.5 Multilevel Analysis
5. MAIN FINDINGS
5.1 Construction of a single SES index
5.2 A preliminary bivariate approach to the association among SES, SABER 11 and SABER PRO
5.3 The power of socioeconomic variables for discrirninating the academic performance
5.4 Assumptions of the MDA
5.5 Logistic regression as an alternative to the MDA
5.6 The effects of SABER 11 and SES in SABER PRO:
MANOVA results
5.7 Assumptions of MANOVA
5.8 Relation between SABER 11 and SABER PRO across universities: A Multilevel approach
5.9 Assumptions of Multilevel
6. DISCUSSION
7. FINAL REMARKS REFERENCES ApPENDICES
Appendix 1
Appendix 2
Appendix 3
