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Quantitative Methods Reading Group

Fortnightly group for PhD students

The Quantitative Methods Reading Group is a fortnightly gathering of PhD students which is starting up this year. At each session, one of the attendees will lead the discussion of an article which they found influential for their field or respective PhD topic. These articles can be reviews of existing methods, a newly developed statistical analysis, or a substantive paper using advanced methodology. For PhD students in later stages of their PhD, this is an excellent opportunity to present their own work, provided that it fits the criteria outlined above. Nevertheless, the presenter does not need to be an expert of the particular field/method, novel and sometimes puzzling applications and approaches can be also proposed for discussion.

The topic and discipline of the articles will vary each week, articles can touch upon quantitative applications regarding Big Data, text analysis, causal inference, structural equation modelling, longitudinal analysis etc. 

Summer Term 2018

1. 2nd May

Wang, X. & Wang, Y. (2018). "'Say Goodbye to the Good Old Days': Anti-corruption, Uncertainty and Firm Behaviors in China". Working paper.

Future sessions will be added in due course.

Lent Term 2018

1. 17th January 
Bell, A. & Jones, K. (2015). Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data. Political Science Research and Methods, 3, 133-153.

2. 31st January
King, G., Lam, P., & Roberts, M. E. (2017). Computer-Assisted Keyword and Document Set Discovery from Unstructured Text. American Journal of Political Science, 61, 1–18.

3. 20th February
Klasnja, M., Titunik, R. (2017). The Incumbency Curse: Weak Parties, Term Limits, and Unfulfilled Accountability. American Political Science Review, 111(1), 129-148.

4. 7th March 
Na, C., Loughran, T.A. & Paternoster, R. (2015). On the Importance of Treatment Effect Heterogeneity in Experimentally-Evaluated Criminal Justice Interventions. Journal of Quantitative Criminology, 31, 289-310.

5. 21st March
Watanabe, K. (2017). Measuring news bias: Russia’s official news agency ITAR-TASS’ coverage of the Ukraine crisis. European Journal of Communication, 32, 224-241.

Michaelmas Term 2017

1. 4th October
Zubizarreta, J.R., Keele, L. (2017). Optimal Multilevel Matching in Clustered Observational Studies: A Case Study of the Effectiveness of Private Schools Under a Large-Scale Voucher System, Journal of the American Statistical Association, 112:518, 547-560.

2. 18th October
Roberts, M. E., Stewart, B. M., Tingley, D., Lucas, C., Leder-Luis, J., Gadarian, S. K., Rand, D. G. (2014). Structural Topic Models for Open-Ended Survey Responses. American Journal of Political Science, 58(4), 1064–1082.

3. 8th November
An, W., Winship, C. (2017). Causal Inference in Panel Data With Application to Estimating Race-of-Interviewer Effects in the General Social Survey. Sociological Methods & Research, 46(1), 68-102.

4. 22 November
Rosenfeld, B., Imai, K., & Shapiro, J. N. (2016). An empirical validation study of popular survey methodologies for sensitive questions. American Journal of Political Science, 60(3), 783-802.

5. 6 December
Nosek, B.A. et al. (2015). Promoting an open research culture. Science, 348(6242):1422-1425. 

Michaelmas term meetings will take place at Columbia House in room 8.13 (COL8.13) on Wednesdays between 12:30-13:30. Complimentary tea and cookies will be provided for each event. If this piqued your interest please get in touch with Chris Pósch (k.p.posch@lse.ac.uk) who will put you on the Reading Group’s mailing list.