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  2. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    In statistics, the logistic model (or logit model) is a statistical model that models the log-odds of an event as a linear combination of one or more independent variables. In regression analysis , logistic regression [ 1 ] (or logit regression ) estimates the parameters of a logistic model (the coefficients in the linear or non linear ...

  3. Ordered logit - Wikipedia

    en.wikipedia.org/wiki/Ordered_logit

    In statistics, the ordered logit model or proportional odds logistic regression is an ordinal regression model—that is, a regression model for ordinal dependent variables—first considered by Peter McCullagh. [1]

  4. Logit - Wikipedia

    en.wikipedia.org/wiki/Logit

    If p is a probability, then p/(1 − p) is the corresponding odds; the logit of the probability is the logarithm of the odds, i.e.: ⁡ = ⁡ = ⁡ ⁡ = ⁡ = ⁡ (). The base of the logarithm function used is of little importance in the present article, as long as it is greater than 1, but the natural logarithm with base e is the one most often used.

  5. Multinomial logistic regression - Wikipedia

    en.wikipedia.org/.../Multinomial_logistic_regression

    The formulation of binary logistic regression as a log-linear model can be directly extended to multi-way regression. That is, we model the logarithm of the probability of seeing a given output using the linear predictor as well as an additional normalization factor, the logarithm of the partition function:

  6. Conditional logistic regression - Wikipedia

    en.wikipedia.org/.../Conditional_logistic_regression

    Logistic regression as described above works satisfactorily when the number of strata is small relative to the amount of data. If we hold the number of strata fixed and increase the amount of data, estimates of the model parameters ( α i {\displaystyle \alpha _{i}} for each stratum and the vector β {\displaystyle {\boldsymbol {\beta ...

  7. Odds - Wikipedia

    en.wikipedia.org/wiki/Odds

    A study on soccer betting found that the probability for the home team to win was generally about 3.4% less than the value calculated from the odds (for example, 46.6% for even odds). It was about 3.7% less for wins by the visitors, and 5.7% less for draws. [14] To understand roulette probabilities and calculate them, you need to know the formula.

  8. One in ten rule - Wikipedia

    en.wikipedia.org/wiki/One_in_ten_rule

    In statistics, the one in ten rule is a rule of thumb for how many predictor parameters can be estimated from data when doing regression analysis (in particular proportional hazards models in survival analysis and logistic regression) while keeping the risk of overfitting and finding spurious correlations low. The rule states that one ...

  9. Generalized linear model - Wikipedia

    en.wikipedia.org/wiki/Generalized_linear_model

    Such a model is a log-odds or logistic model. Generalized linear models cover all these situations by allowing for response variables that have arbitrary distributions (rather than simply normal distributions ), and for an arbitrary function of the response variable (the link function ) to vary linearly with the predictors (rather than assuming ...