Interpreting Probit Analysis
نویسنده
چکیده
Regression via ordinary least squares (OLS) is a commonly applied statistical technique in political science. However, when the dependent variable is dichotomous (0-1) rather than continuous, ordinary least squares becomes an inefficient estimation technique, and the underlying linear probability model (LPM) that is being estimated represents a poor apriori choice of model specification (Aldrich and Nelson, 1984). The linear probability model assumes that the expected value of the dependent variable, or the probability that the dependent variable takes the value 1, is a linear combination of some set of independent variables. Or, E[Yi] = β0 + β1x1i + β2x2i + ...+ βkxki + ui (1)
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