Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

The logit and probit models have become critical parts of the management researcher's analytical arsenal, growing rapidly from almost no use in the 1980s to appearing in 15% of all articles published ...

The standard linear regression model does not apply when the effect of one explanatory variable on the dependent variable depends on the value of another explanatory variable. In this case, the ...

Balvir Singh, A. L. Nagar, N. K. Choudhry and Baldev Raj The International Economic Review was established in 1960 by two of the most active and acclaimed scholars in the economics profession: Michio ...

Beside the model, the other input into a regression analysis is some relevant sample data, consisting of the observed values of the dependent and explanatory variables for a sample of members of the ...

Vivienne Pham (School Economics, La Trobe University) and David Prentice (School of Economics, La Trobe University) describe A Random Coefficients Logit Analysis of the Counterfactual: A Merger and ...