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Logistic Regression in Rare Events Data
Open accessAbstract
We study rare events data, binary dependent variables with dozens to thousands of times fewer ones (events, such as wars, vetoes, cases of political activism, or epidemiological infections) than zeros (“nonevents”). In many literatures, these variables have proven difficult to explain and predict, a problem that seems to have at least two sources. First, popular statistical procedures, such as logistic regression, can sharply underestimate the probability of rare events. We recommend corrections that outperform existing methods and change the estimates of absolute and relative risks by as much as some estimated effects reported in the literature. Second, commonly used data collection strategies are grossly inefficient for rare events data. The fear of collecting data with too few events has led to data collections with huge numbers of observations but relatively few, and poorly measured, explanatory variables, such as in international conflict data with more than a quarter-million dyads, only a few of which are at war. As it turns out, more efficient sampling designs exist for making valid inferences, such as sampling all available events (e.g., wars) and a tiny fraction of nonevents (peace). This enables scholars to save as much as 99% of their (nonfixed) data collection costs or to collect much more meaningful explanatory variables. We provide methods that link these two results, enabling both types of corrections to work simultaneously, and software that implements the methods developed.
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“In columns 5 to 7, we report results using this estimator.The two modernization variables remain individually signi…cant and jointly signi…cant when entered together.”
From From Open to Secret Ballot: Vote Buying and Modernization (2012) · cites this paper as King and Zeng (2001)
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Cites
Designing Social Inquiry: Scientific Inference in Qualitative Research
King, G., Keohane, R. O., & Verba, S. (1994) · Princeton University Press · doi:10.1515/9781400821211 · Cited by 7,225
Self-citation
Research works printed but not linked: 47
- Verba, 1995, Voice and Equality: Civic Voluntarism in American Politics, 10.2307/j.ctv1pnc1k7 · DOI
- 10.1007/978-1-4612-4024-2 · DOI
- Smith, 1998, Bayesian Statistics
- 10.1111/0020-8833.00113 · DOI
- 10.2307/2585396 · DOI
- Scott, 1986, Fitting Logistic Models Under Case-Control or Choice Based Sampling, Journal of the Royal Statistical Society, B, 48, 170, 10.1111/j.2517-6161.1986.tb01400.x · DOI
- 10.1017/CBO9780511812651 · DOI
- 10.1093/biomet/66.3.403 · DOI
- 10.1002/sim.4780140806 · DOI
- 10.2307/2938740 · DOI
- Manski, 1981, Structural Analysis of Discrete Data with Econometric Applications
- 10.2307/1914121 · DOI · Paper page
- Manski, 1999, Nonlinear Statistical Inference: Essays in Honor of Takeshi Amemiya
- 10.1016/0304-4076(94)01698-4 · DOI
- 10.1007/978-1-4899-3242-6 · DOI · Paper page
- 10.2307/2669316 · DOI · Paper page
- King Gary , and Zeng Langche . 2000b. “Explaining Rare Events in International Relations.” International Organization (in press).
- King Gary , and Zeng Langche . 2000a. “Inference in Case-Control Studies with Limited Auxilliary Information” (in press). (Preprint at http://Gking.harvard.edu.)
- 10.2307/2951544 · DOI
- 10.1080/01621459.1985.10478165 · DOI
- 10.1017/CBO9780511521713 · DOI
- 10.1007/978-1-4899-4467-2 · DOI
- 10.1093/biomet/80.1.27 · DOI · Paper page
- 10.2307/1912755 · DOI
- Bueno de Mesquita, 1992, War and Reason: Domestic and International Imperatives, 10.2307/j.ctt1bh4dhm · DOI
- Bueno de Mesquita, 1981, The War Trap
- 10.1080/01621459.1996.10476660 · DOI
- 10.2307/1913609 · DOI
- 10.1214/ss/1177011454 · DOI
- Breslow, 1980, Statistical Methods in Cancer Research
- 10.1002/sim.4780020108 · DOI
- Rothman, 1998, Modern Epidemiology
- Cosslett, 1981b, Structural Analysis of Discrete Data with Econometric Applications
- Rosenau, 1976, In Search of Global Patterns
- 10.1017/CBO9780511583483 · DOI
- Levy, 1989, Behavior, Society, and Nuclear War, 1, 2120
- McCullagh, 1987, Tensor Methods in Statistics
- Mehta, 1997, Exact Inference for Categorical Data
- 10.1177/0049124189017003003 · DOI
- 10.2307/1957394 · DOI
- 10.1017/S0003055400220078 · DOI
- Greene, 1993, Econometric Analysis
- 10.1016/0378-3758(93)E0091-T · DOI
- 10.1177/0193841X8801200301 · DOI
- Lancaster, 1996b, Efficient Estimation and Stratified Sampling, Journal of Econometrics, 74, 289, 10.1016/0304-4076(95)01756-9 · DOI
- 10.1002/(SICI)1097-0258(19970315)16:5<545::AID-SIM421>3.0.CO;2-3 · DOI
- Cordeiro, 1991, Bias Correction in Generalized Linear Models, Journal of the Royal Statistical Society, B, 53, 629, 10.1111/j.2517-6161.1991.tb01852.x · DOI
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BackgroundEstimating bank default with generalised extreme value regression models
Calabrese, R., & Giudici, P. (2015) · Journal of the Operational Research Society · doi:10.1057/jors.2014.106 · Cited by 69
“See, for example, the papers by Koopman et al (2012) and, more recently, Mare (2012) and Kanno (2013) who applied these kinds of models, respectively, to the Italian and Japanese banking systems.”
BackgroundMethodSaarimaa, T., & Tukiainen, J. (2013) · Political Science Research and Methods · doi:10.1017/psrm.2013.25 · Cited by 68
Chen, A.-Q., Wu, H.-L., Wang, T., Wang, X.-Z., Sun, H., & Yu, R.-Q. (2022) · Talanta: The International Journal of Pure and Applied Analytical Chemistry · doi:10.2139/ssrn.4086611 · Cited by 67
Dunlop, A. L., Satten, G. A., Hu, Y., Knight, A. K., Hill, C. C., Wright, M. L., Smith, A. K., Read, T. D., Pearce, B. D., & Corwin, E. J. (2021) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2021.641005 · Cited by 86
“We used the Firth correction for the relatively rare occurrence of the gestational age outcomes of interest (especially sPTB) among those with noniners Lactobacillus CST, which reduces small sample bias in maximum likelihood estimation (King and Zeng, 2001).”
MethodOksanen, A., Miller, B., Savolainen, I., Sirola, A., Demant, J., Kaakinen, M., & Zych, I. (2020) · European Journal of Psychology Applied to Legal Context · doi:10.5093/ejpalc2021a5 · Cited by 67
“These analyses were conducted by using penalized maximum likelihood logistic regression (i.e., Firth method) to reduce potential small-sample bias (Firth, 1993; Greenland & Mansournia, 2015; King & Zeng, 2001).”
MethodLanguage friction and partner selection in cross-border R&D alliance formation
Joshi, A. M., & Lahiri, N. (2014) · Journal of International Business Studies · doi:10.1057/jibs.2014.56 · Cited by 68
The Impact of Vicarious Experience on Foreign Location Strategy
Jiang, G. F., Holburn, G. L. F., & Beamish, P. W. (2013) · Journal of International Management · doi:10.1016/j.intman.2013.10.005 · Cited by 74
Driving-Induced Neurological Biomarkers in an Advanced Driver-Assistance System
Hussain, I., Young, S., & Park, S. (2021) · Italian National Conference on Sensors · doi:10.3390/s21216985 · Cited by 66
Raise Taxes, Cut Services, or Lay Off Staff: Citizens in the Fiscal Retrenchment Process
Jimenez, B. S. (2014) · Journal of Public Administration Research and Theory · doi:10.1093/jopart/mut018 · Cited by 66
Statistical modeling methods: challenges and strategies
Henley, S. S., Golden, R. M., & Kashner, T. M. (2019) · Biostatistics & Epidemiology · doi:10.1080/24709360.2019.1618653 · Cited by 70
Christ, T., Wang, X. C., Chiu, M.-M., & Cho, H. (2019) · Early Childhood Research Quarterly · doi:10.1016/j.ecresq.2019.01.003 · Cited by 65
Business failure, efficiency, and volatility: Evidence from the European insurance industry
Eling, M., & Jia, R. (2018) · International Review of Financial Analysis · doi:10.1016/j.irfa.2018.07.007 · Cited by 78
Chen, H., & Xie, F.-J. (2018) · Journal of Management Analytics · doi:10.1080/23270012.2018.1478329 · Cited by 65
Detges, A. (2014) · Political Geography · doi:10.1016/j.polgeo.2014.06.003 · Cited by 65
“This might induce biases in the regression estimates, as explained by King and Zeng (2001).”
MethodCrowder-Meyer, M. (2018) · Political Behavior · doi:10.1007/s11109-018-9498-9 · Cited by 64
Safeguarding Democracy: Powersharing and Democratic Survival
Graham, B. A. T., Miller, M. K., & Strøm, K. W. (2017) · American Political Science Review · doi:10.1017/s0003055417000326 · Cited by 133
“Using probits for such small likelihoods can cause statistical problems (see King and Zeng 2001) that we avoid by analyzing 5-year transition probabilities.”
Gattermann, K., & Hefftler, C. (2015) · doi:10.1080/01402382.2014.990696 · Cited by 64
Educational Mobility of Second-generation Turks
Schnell, P. (2014) · Amsterdam University Press eBooks · doi:10.26530/oapen_508001 · Cited by 66
Lee, J., Zee, B. C.-Y., & Li, Q. (2013) · PLoS ONE · doi:10.1371/journal.pone.0075699 · Cited by 60
The effect of informal and formal institutions on foreign market entry selection and performance
Fuentelsaz, L., Garrido, E., & Maícas, J. P. (2020) · Journal of International Management · doi:10.1016/j.intman.2020.100735 · Cited by 69
Language Style Similarity and Friendship Networks
Kovács, B., & Kleinbaum, A. M. (2018) · Psychological Science · doi:10.1177/0956797619894557 · Cited by 75
“Because the network was large and sparse (< 1% of possible friendship ties were present), we used a case-cohort design (King & Zeng, 2001; Kleinbaum et al., 2013), sampling all observations with an observed tie but only a fraction of the nonpresent ties.”
MethodZhang, S., Xiao, K., Carranza, E. J., & Yang, F. (2018) · Natural Resources Research · doi:10.1007/s11053-018-9425-0 · Cited by 63
Should there be lower taxes on patent income?
Gaessler, F., Hall, B. H., & Harhoff, D. (2018) · Research Policy · doi:10.1920/wp.ifs.2018.1918 · Cited by 63
Youth bulge and civil war: Why a country’s share of young adults explains only non-ethnic wars
Yair, O., & Miodownik, D. (2014) · Conflict Management and Peace Science · doi:10.1177/0738894214544613 · Cited by 85
“However, their sample of country-years was very small, combined with a selection on the dependent variable (on these points, see also King and Zeng, 2001b).”
BackgroundMethodBunea, A., & Thomson, R. (2015) · doi:10.1111/gove.12119 · Cited by 63
Metadata
- Authors
- King, G., & Zeng, L.
- Affiliations
- Harvard University (US)
- George Washington University (US)
- ORCID
- King, Gary
- Venue
- Political Analysis
- Publisher
- Cambridge University Press (CUP)
- Published
- 2001
- Volume
- 9
- Issue
- 2
- Pages
- 137-163
- ISSN
- 1047-1987 (ISSN-L)
- 1476-4989
- OpenAlex
- W2163848058
- Cited by
- 4,316
- References
- 0
- Citations by year
- 2026: 273 · 2025: 223 · 2024: 261 · 2023: 235 · 2022: 277 · 2021: 362 · 2020: 316 · 2019: 307 · 2018: 236 · 2017: 176 · 2016: 205 · 2015: 189 · 2014: 238 · 2013: 185 · 2012: 142
- FWCI
- 61.75
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Political Analysis (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Science Foundation (9729884, 9753126)
- University of Cambridge
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Survey Sampling and Estimation Techniques
- Keywords
- rare events, logistic regression, binary dependent variables, sampling design, event sampling, war, risk estimation, data collection efficiency
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