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  2. Multinomial probit - Wikipedia

    en.wikipedia.org/wiki/Multinomial_probit

    The multinomial probit model is a statistical model that can be used to predict the likely outcome of an unobserved multi-way trial given the associated explanatory variables. In the process, the model attempts to explain the relative effect of differing explanatory variables on the different outcomes.

  3. Multivariate probit model - Wikipedia

    en.wikipedia.org/wiki/Multivariate_probit_model

    In statistics and econometrics, the multivariate probit model is a generalization of the probit model used to estimate several correlated binary outcomes jointly. For example, if it is believed that the decisions of sending at least one child to public school and that of voting in favor of a school budget are correlated (both decisions are binary), then the multivariate probit model would be ...

  4. Probit model - Wikipedia

    en.wikipedia.org/wiki/Probit_model

    In statistics, a probit model is a type of regression where the dependent variable can take only two values, for example married or not married. The word is a portmanteau , coming from prob ability + un it . [ 1 ]

  5. Heckman correction - Wikipedia

    en.wikipedia.org/wiki/Heckman_correction

    Heckman's correction involves a normality assumption, provides a test for sample selection bias and formula for bias corrected model. Suppose that a researcher wants to estimate the determinants of wage offers, but has access to wage observations for only those who work.

  6. Discrete choice - Wikipedia

    en.wikipedia.org/wiki/Discrete_choice

    This third requirement distinguishes discrete choice analysis from forms of regression analysis in which the dependent variable can (theoretically) take an infinite number of values. As an example, the choice set for a person deciding which mode of transport to take to work includes driving alone, carpooling, taking bus, etc. The choice set is ...

  7. Ordinal regression - Wikipedia

    en.wikipedia.org/wiki/Ordinal_regression

    [1] [2] Examples of ordinal regression are ordered logit and ordered probit. Ordinal regression turns up often in the social sciences, for example in the modeling of human levels of preference (on a scale from, say, 1–5 for "very poor" through "excellent"), as well as in information retrieval.

  8. Choice modelling - Wikipedia

    en.wikipedia.org/wiki/Choice_modelling

    For example the Latin square 16 17 design allows the estimation of all main effects of a product that could have up to 16 17 (approximately 295 followed by eighteen zeros) configurations. Furthermore this could be achieved within a sample frame of only around 256 respondents. Below is an example of a much smaller design. This is 3 4 main ...

  9. Methodology of econometrics - Wikipedia

    en.wikipedia.org/wiki/Methodology_of_Econometrics

    Econometrics may use standard statistical models to study economic questions, but most often they are with observational data, rather than in controlled experiments. [10] In this, the design of observational studies in econometrics is similar to the design of studies in other observational disciplines, such as astronomy, epidemiology, sociology and political science.

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