ReLogit: Rare Events Logistic Regression
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 shar ply 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 repor ted 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 obser vations but relatively few, and poorly measured, explanator y 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 explanator y variables. We provide methods that link these two results, enabling both types of corrections to work simultaneously, and software that implements the methods developed.
Volume (Year): 008 (2003)
Issue (Month): i02 ()
|Contact details of provider:|| Web page: http://www.jstatsoft.org/|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Imbens, Guido W, 1992.
"An Efficient Method of Moments Estimator for Discrete Choice Models with Choice-Based Sampling,"
Econometric Society, vol. 60(5), pages 1187-1214, September.
- Imbens, G.W., 1990. "An Efficient Method of Moments Estimator for Discrete Choice Models with Choice-Based Sampling," Discussion Paper 1990-9, Tilburg University, Center for Economic Research.
- Imbens, G.W., 1991. "An Efficient Method Of Moments Estimator For Discrete Choice Models With Choice-Based Sampling," Harvard Institute of Economic Research Working Papers 1546, Harvard - Institute of Economic Research.
- Imbens, G.W., 1990. "An Efficient Method Of Moments Estimator For Descrete Choice Models With Choice-Based Sampling," Papers 9009, Tilburg - Center for Economic Research.
- Amemiya, Takeshi & Vuong, Quang H, 1987. "A Comparison of Two Consistent Estimators in the Choice-based Sampling Qualitative Response Model," Econometrica, Econometric Society, vol. 55(3), pages 699-702, May.
- Imbens, Guido W. & Lancaster, Tony, 1996. "Efficient estimation and stratified sampling," Journal of Econometrics, Elsevier, vol. 74(2), pages 289-318, October.
- Imbens, G. & Lancaster, T., 1991. "Efficient Estimation and Stratified Sampling," Papers 9145, Tilburg - Center for Economic Research.
- Imbens, G.W. & Lancaster, T., 1991. "Efficient estimation and stratified sampling," Discussion Paper 1991-45, Tilburg University, Center for Economic Research.
- Imbens, G. & Lancaster, T., 1991. "Efficient Estimation And Stratified Sampling," Harvard Institute of Economic Research Working Papers 1545, Harvard - Institute of Economic Research.
- King, Gary & Zeng, Langche, 2001. "Explaining Rare Events in International Relations," International Organization, Cambridge University Press, vol. 55(03), pages 693-715, June.
- Paul W. Holland & Donald B. Rubin, 1988. "Causal Inference in Retrospective Studies," Evaluation Review, , vol. 12(3), pages 203-231, June.
- Manski, Charles F & Lerman, Steven R, 1977. "The Estimation of Choice Probabilities from Choice Based Samples," Econometrica, Econometric Society, vol. 45(8), pages 1977-1988, November. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:jss:jstsof:v:008:i02. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.