2003
DOI: 10.18637/jss.v008.i02
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Logistic Regression in Rare Events Data

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Cited by 1,224 publications
(1,636 citation statements)
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“…This is a feasible assumption in Finland, where farmers do not have a history of moving from one place to another. 8 It is known that rare events of this kind may not be captured by a logit model, and the model may underestimate their probability (King and Zeng 2001). However, based on King and Zeng's (2001) work, rare events were not a problem in our analysis, as the proportion of future sellers among all land owners varied from 13.9% to 25.8%, and the number of observations was between 532 and 833.…”
Section: Logit Models For Sale Preferencesmentioning
confidence: 90%
See 1 more Smart Citation
“…This is a feasible assumption in Finland, where farmers do not have a history of moving from one place to another. 8 It is known that rare events of this kind may not be captured by a logit model, and the model may underestimate their probability (King and Zeng 2001). However, based on King and Zeng's (2001) work, rare events were not a problem in our analysis, as the proportion of future sellers among all land owners varied from 13.9% to 25.8%, and the number of observations was between 532 and 833.…”
Section: Logit Models For Sale Preferencesmentioning
confidence: 90%
“…8 It is known that rare events of this kind may not be captured by a logit model, and the model may underestimate their probability (King and Zeng 2001). However, based on King and Zeng's (2001) work, rare events were not a problem in our analysis, as the proportion of future sellers among all land owners varied from 13.9% to 25.8%, and the number of observations was between 532 and 833. 9 As a first step in selecting socioeconomic variables for the logit models for selling decisions, we used correlation analysis, cross tabulation, and chi-squared statistics.…”
Section: Logit Models For Sale Preferencesmentioning
confidence: 90%
“…Due to the low number of participants (3.5%) declaring having accessed self-tests, the characteristics of this subgroup were analysed using logistic regression for rare events 26. Model building was in two steps: first, a list of potential explanatory variables was defined and a univariate analysis was conducted on these; variables with a p value inferior to a predefined threshold (0.20) were then included in a multivariate analysis and a backward selection method based on the log-likelihood ratio test was used to select significant variables in the multivariate model (significance level α=0.05).…”
Section: Methodsmentioning
confidence: 99%
“…Robust standard errors were used to guard against model misspecification [8]. Estimates were bias-adjusted for rare events [9]. All P values are 2-sided.…”
Section: Methodsmentioning
confidence: 99%