Logit Models from Economics and Other Fields

By J. Cramer. 2003

168 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

Citations in the corpus

Assessing the effect of prevalence on the predictive performance of species distribution models using simulated data (2011, background): “, 2006); (2) a threshold based on the prevalence of the species calibration data (Cramer, 2003; Franklin et al., 2009); and (3) a fixed threshold value of 0.”
Selecting thresholds of occurrence in the prediction of species distributions (2005, methodology): “Cramer (2003) also realized the problem with fixed threshold approach, especially taking 0.5 as the threshold.”
Comparing Regression Coefficients Between Models using Logit and Probit: A New Method (2010, methodology): “This comes about because, in nonlinear probability models, the error variance is not independently identified and is fixed at a given value (Cramer 2003:22).2 This identification restriction is well known in the literature on limited dependent variable models (Yatchew and Griliches 1985, Long 1997;…”
An Almost Integration-free Approach to Ordered Response Models (2006, methodology): “Logit analysis (see Cramer (2003) for a recent survey).”
The distribution of deep-sea sponge aggregations in the North Atlantic and implications for their effective spatial management (2016, methodology): “Five thresholding methods recommended by Liu et al., (2005) were considered for each model: sensitivity-specificity equality, sensitivity-specificity sum maximization, ROC-plot-252 based approaches (Cantor et al., 1999), prevalence, and average probability/suitability approaches (Cramer 2003).”