params.json

{
  "name": "Vkme16",
  "tagline": "Materialer til faget \"Videregående kvantitative metoder i studiet af politisk adfærd\"",
  "body": "# Videregående kvantitative metoder i studiet af politisk adfærd\r\n\r\nDette repository ('repo') samler materialer til faget \"Videregående kvantitative metoder i studiet af politisk adfærd\".\r\n\r\n### Indhold i dette repo\r\n\r\n`data`: Datasæt til brug i undervisningen\r\n\r\n`examples`: Kodeeksempler til illustration af forskellige funktioner\r\n\r\n`extra`: Ekstramaterialer såsom supplerende slides og præsentationer\r\n\r\n`midterm`: Materialer ifm. fagets midterm-opgave\r\n\r\n`scripts`: R-scripts anvendt i undervisningen\r\n\r\n`slides`: Slides til undervisningsgangene\r\n\r\n`workshop`: Materialer ifm. fagets workshop\r\n\r\n## Undervisningsplan\r\n\r\nGang | Dato | Tema | Litteratur | Case\r\n---|---|---|---|---\r\n1 | 5/9 | Introduktion til R | Imai kap 1 |\r\n2 | 12/9 | Regression I: OLS | GH kap 3, MM kap 2 | Gilens & Page (2014)\r\n3 | 26/9 | Regression II: Paneldata | GH kap 11 | Larsen et al. (2016)\r\n4 | 29/9 | Regression III: Multileveldata, interaktioner | GH kap 12 | Berkman & Plutzer (2011)\r\n5 | 3/10 | Introduktion til kausal inferens | Hariri (2012), Samii (2016) |\r\n6 | 10/10 | Matching | Justesen & Klemmensen (2014) | Ladd & Lenz (2009)\r\n  | 17/10 | *Efterårsferie* | |\r\n7 | 24/10 | Eksperimenter I | MM kap 1, GG kap 1+2 | Gerber, Green & Larimer (2008)\r\n8 | 31/10 | Eksperimenter II | GG kap 3+4+5 | Gerber & Green (2000)\r\n9 | 14/11 | Instrumentvariable | MM kap 3 | Arunachalam & Watson (2016)\r\n10 | 14/11 | Regressionsdiskontinuitetsdesigns | MM kap 4 | Eggers & Hainmueller (2009)\r\n11 | 21/11 | Difference-in-differences | MM kap 5 | Enos (2016)\r\n12 | 28/11 | 'Big data' og maskinlæring | Harford (2014), Grimmer (2015), Varian (2014), Athey & Imbens (2016) |\r\n13 | 5/12 | Scraping af data fra online-kilder | MRMN kap 9+14 |\r\n14 | 12/12 | Tekst som data | Grimmer & Stewart (2013), Imai kap 5, Benoit & Nulty (2016) | Hjorth et al. (2015)\r\n\r\n<!-- 3 | 19/9 | Regression II: Binære data | GH kap 5 | -->\r\n\r\n### Tidspunkt(er) og lokale(r)\r\n\r\nUndervisningen finder sted mandage 10-12 i lokale 1.0.10. Bemærk dog flg. undtagelser:\r\n\r\n- Gang 1 og 7 finder dog sted kl. 16-18, lokale 2.2.42.\r\n- Gang 4 finder sted torsdag d. 29. september kl. 12-14, lokale 2.0.30.\r\n- Gang 10 finder sted mandag d. 14. november kl. 13-15, lokale 2.1.02\r\n\r\n## Litteratur\r\n\r\n### Bøger\r\n\r\nGH: Gelman, A., & Hill, J. (2006). *Data analysis using regression and multilevel/hierarchical models*. Cambridge University Press.\r\n\r\nGG: Gerber, A. S., & Green, D. P. (2012). *Field experiments: Design, analysis, and interpretation*. WW Norton.\r\n\r\nImai: Imai, K. (2016): *A First Course in Quantitative Social Science*. Unpublished manuscript.\r\n\r\nMM: Angrist, J. D., & Pischke, J. S. (2014). *Mastering 'metrics: The path from cause to effect*. Princeton University Press.\r\n\r\nMRMN: Munzert, S., Rubba, C., Meißner, P., & Nyhuis, D. (2014). *Automated data collection with R: A practical guide to web scraping and text mining*. John Wiley & Sons.\r\n\r\n### Artikler\r\n\r\n\r\nAthey, S., & Imbens, G. (2016). The State of Applied Econometrics-Causality and Policy Evaluation. *arXiv preprint* arXiv:1607.00699.\r\n\r\nBenoit, K., & Nulty, P. (2016) [Getting Started with quanteda](https://cran.r-project.org/web/packages/quanteda/vignettes/quickstart.html)\r\n\r\nGrimmer, J. (2015). We are all social scientists now: how big data, machine learning, and causal inference work together. *PS: Political Science & Politics*, 48(01), 80-83.\r\n\r\nGrimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. *Political Analysis*, 21(3), 267-297.\r\n\r\nHarford, T. (2014). Big data: A big mistake?. *Significance*, 11(5), 14-19. Chicago\r\n\r\nHariri, J. G. (2012). Kausal inferens i statskundskaben. *Politica*, 44(2), 184-201.\r\n\r\nJustesen, M. K., & Klemmensen, R. (2014). Sammenligning af sammenlignelige observationer. *Politica*, 46(1), 60-78.\r\n\r\nSamii, C. (2016). Causal empiricism in quantitative research. *Journal of Politics* 78(3): 941–955.\r\n\r\nVarian, H. R. (2014). Big data: New tricks for econometrics. *The Journal of Economic Perspectives*, 28(2), 3-27.\r\n\r\n### Cases\r\n\r\nArunachalam, R., & Watson, S. (2016). Height, Income and Voting. *British Journal of Political Science*, 46(03), 1–20.\r\n\r\nBerkman, M. B., & Plutzer, E. (2011). Defeating creationism in the courtroom, but not in the classroom. *Science*, 331(6016), 404-405.\r\n\r\n<!-- Bond, R. M., Fariss, C. J., Jones, J. J., Kramer, A. D., Marlow, C., Settle, J. E., & Fowler, J. H. (2012). A 61-million-person experiment in social influence and political mobilization. *Nature*, 489(7415), 295-298. -->\r\n\r\n<!-- Dinesen, P. T., & Sønderskov, K. M. (2012). Trust in a time of increasing diversity: On the relationship between ethnic heterogeneity and social trust in Denmark from 1979 until today. *Scandinavian Political Studies*, 35(4), 273-294. -->\r\n\r\nEggers, A. C., & Hainmueller, J. (2009). MPs for sale? Returns to office in postwar British politics. *American Political Science Review*, 103(04), 513-533.\r\n\r\nEnos, R. D. (2016). What the demolition of public housing teaches us about the impact of racial threat on political behavior. *American Journal of Political Science*, 60(1), 123-142.\r\n\r\nGerber, A. S., & Green, D. P. (2000). The effects of canvassing, telephone calls, and direct mail on voter turnout: A field experiment. American Political Science Review, 94(03), 653-663.\r\n\r\nGilens, M., & Page, B. I. (2014). Testing theories of American politics: Elites, interest groups, and average citizens. *Perspectives on politics*, 12(03), 564-581.\r\n\r\nGerber, A. S., Green, D. P., & Larimer, C. W. (2008). Social pressure and voter turnout: Evidence from a large-scale field experiment. *American Political Science Review*, 102(01), 33-48.\r\n\r\nHjorth, F., Klemmensen, R., Hobolt, S., Hansen, M. E., & Kurrild-Klitgaard, P. (2015). Computers, coders, and voters: Comparing automated methods for estimating party positions. *Research & Politics*, 2(2).\r\n\r\nLadd, J. M., & Lenz, G. S. (2009). Exploiting a rare communication shift to document the persuasive power of the news media. *American Journal of Political Science*, 53(2), 394-410.\r\n\r\nLarsen, M. V., Hjorth, F., Dinesen, P. & Sønderskov, K. M. (2016). Housing Bubbles and Support for Incumbents. *Annual Meeting of the American Political Science Association*.\r\n",
  "note": "Don't delete this file! It's used internally to help with page regeneration."
}