SOS9009 - Spring 2020

Syllabus/achievement requirements

 

COURSE LITERATURE

Each module includes a reading list. These readings are books and journal articles. Please note that you DO NOT NEED TO purchase these books. They may come in handy as reference works if you will do sophisticated Stata programming in the future. It is recommended to not buy any books until you have evaluated whether or not they will be useful (enough) to you.

Module A. Advanced stata programming

 

Most students at ISS use Stata. This module introduces advanced topics in Stata programming. These will be highly valuable skills when conducting own research or thesis work. Examples include progammatical manipulation of analysis results, automation of tasks, and producing publication-ready tables and graphs for your thesis.

Literature:

Module B. Quantile regression using Stata

 

This module introduces quantile regression models. These techniques allow researchers to examine statistical relationships effects that vary in strength over the outcome distribution. There are many instances where social scientists expect that effects vary across the outcome distribution. For example, may one ask whether effects of homework assignements on school grades are strongest for the best-performing students. Quantile regression is a tool that allow one to depart from models of the mean only.

Literature:

Supplementary literature:

Module C. Biometric models

 

This module introduces biometric models (“twin models”, and other related models) from a sociological standpoint. What can we use these models for, and how do we use them? The module provides some introductory lecture material, and practical exercises in estimating and interpreting biometric models. It also offers a simple introduction to molecular genetics approaches in social sciences.

Literature:

Supplementary literature:

  • Polderman, T. J., Benyamin, B., De Leeuw, C. A., Sullivan, P. F., Van Bochoven, A., Visscher, P. M., & Posthuma, D. (2015). Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nature genetics, 47(7), 702.
  • Heath, A. C., Berg, K., Eaves, L. J., Solaas, M. H., Corey, L. A., Sundet, J., … & Nance, W. E. (1985). Education policy and the heritability of educational attainment. Nature, 314(6013), 734-736.
  • D’Onofrio, B. M., Turkheimer, E. N., Eaves, L. J., Corey, L. A., Berg, K., Solaas, M. H., & Emery, R. E. (2003). The role of the children of twins design in elucidating causal relations between parent characteristics and child outcomes. Journal of Child Psychology and Psychiatry, 44(8), 1130-1144.
  • Baier, T., & Lang, V. (2019). The social stratification of environmental and genetic influences on education: New evidence using a register-based twin sample. Sociological Science, 6, 143-171.
  • Figlio, D. N., Freese, J., Karbownik, K., & Roth, J. (2017). Socioeconomic status and genetic influences on cognitive development. Proceedings of the National Academy of Sciences, 114(51), 13441-13446.

Nielsen, F., & Roos, J. M. (2015). Genetics of Educational Attainment and the Persistence of Privilege at the Turn of the 21st Century. Social Forces, 94(2), 535-561.

Module D. Fixed and Random Effects Regression Models using sibling and panel data

 

This module is a workshop in one of the workhorses of empirical social science, panel data analysis. Emphasis are on fixed effects approaches, but also cover random effects to some extent. Examples are taken from the broader sociological literature on social stratification.

Literature:

Supplementary literature:

  • Cameron, A. C., and Trivedi, P. K. (2010). Microeconometrics Using Stata: Revised Edition (2 edition). Stata Press.
  • Rabe-Hesketh, Sophia & Skrondal, Anders 2008. Multilevel and longitudinal modelling using Stata. Second edition. Stata Press.

Some examples of applications in sociological stratification research:

  • Andersen, P. L., and Hansen, M. N. (2012). Class and Cultural Capital—The Case of Class Inequality in Educational Performance. European Sociological Review, 28(5), 607–621. https://doi.org/10.1093/esr/jcr029
  • Elstad, J. I., and Bakken, A. (2015). The effects of parental income on Norwegian adolescents’ school grades: A sibling analysis. Acta Sociologica, 58(3), 265–282. https://doi.org/10.1177/0001699315594411
  • Erola, J., Jalonen, S., and Lehti, H. (2016). Parental education, class and income over early life course and children’s achievement. Research in Social Stratification and Mobility, 44, 33–43. https://doi.org/10.1016/j.rssm.2016.01.003
  • H?llsten, M., and Pfeffer, F. T. (2017). Grand Advantage: Family Wealth and Grandchildren’s Educational Achievement in Sweden. American Sociological Review. https://doi.org/10.1177/0003122417695791
  • J?ger, M. M. (2011). Does Cultural Capital Really Affect Academic Achievement? New Evidence from Combined Sibling and Panel Data. Sociology of Education, 84(4), 281–298. https://doi.org/10.1177/0038040711417010
  • Wiborg, ?. N., and Hansen, M. N. (2018). The Scandinavian model during increasing inequality: Recent trends in educational attainment, earnings and wealth among Norwegian siblings. Research in Social Stratification and Mobility, 56, 53–63. https://doi.org/10.1016/j.rssm.2018.06.006

Supplementary literature on empirical applications of FE and RE:

  • Conley, D., Domingue, B. W., Cesarini, D., Dawes, C., Rietveld, C. A., and Boardman, J. D. (2015). Is the Effect of Parental Education on Offspring Biased or Moderated by Genotype? Sociological Science, 2, 82–105. https://doi.org/10.15195/v2.a6
  • Dahl, S.-?., Hansen, H.-T., and Olsen, K. M. (2010). Sickness Absence among Immigrants in Norway, 1992—2003. Acta Sociologica, 53(1), 35–52. https://doi.org/10.1177/0001699309357841
  • Gr?tz, M., Barclay, K. J., Wiborg, ?., Lyngstad, T., Karhula, A., Erola, J., Pr?g, P., Laidley, T., and Conley, D. (2019). Universal family background effects on education across and within societies (WP-2019-007; MPIDR Working Papers). Max Planck Institute for Demographic Research, Rostock, Germany. https://ideas.repec.org/p/dem/wpaper/wp-2019-007.html
  • Gr?tz, M., and Torche, F. (2016). Compensation or Reinforcement? The Stratification of Parental Responses to Children’s Early Ability. Demography, 53(6), 1883–1904. https://doi.org/10.1007/s13524-016-0527-1
  • Hermansen, A. S., and Birkelund, G. E. (2015). The Impact of Immigrant Classmates on Educational Outcomes. Social Forces, 94(2), 615–646. https://doi.org/10.1093/sf/sov073
  • J?ger, M. M., and M?llegaard, S. (2017). Cultural capital, teacher bias, and educational success: New evidence from monozygotic twins. Social Science Research, 65, 130–144. https://doi.org/10.1016/j.ssresearch.2017.04.003
  • Laidley, T., Vinneau, J., and Boardman, J. D. (2019). Individual and Social Genomic Contributions to Educational and Neighborhood Attainments: Geography, Selection, and Stratification in the United States. Sociological Science, 6, 580–608. https://doi.org/10.15195/v6.a22
  • Petersen, T., Penner, A. M., and H?gsnes, G. (2014). From Motherhood Penalties to Husband Premia: The New Challenge for Gender Equality and Family Policy, Lessons from Norway. American Journal of Sociology, 119(5), 1434–1472. https://doi.org/10.1086/674571
  • Petersen, T., Penner, A. M., and H?gsnes, G. (2014). From Motherhood Penalties to Husband Premia: The New Challenge for Gender Equality and Family Policy, Lessons from Norway. American Journal of Sociology, 119(5), 1434–1472. https://doi.org/10.1086/674571
  • Vauhkonen, T., Kallio, J., Kauppinen, T. M., and Erola, J. (2017). Intergenerational accumulation of social disadvantages across generations in young adulthood. Research in Social Stratification and Mobility, 48, 42–52. https://doi.org/10.1016/j.rssm.2017.02.001

Supplementary literature on advances within the RE and FE-design:

Published Feb. 18, 2020 1:12 PM - Last modified Feb. 18, 2020 1:12 PM
E-mail this page
Error: uriis required