A probit-model is a regression technique for binary dependent variables where the latent variable y* is modeled as a linear combination of predictors (y* = Xβ + ε) with ε ~ N(0,1), and the observed binary outcome y equals 1 when y* > 0 and 0 otherwise. The probability P(y=1|x) = Φ(Xβ) where Φ is the standard normal cumulative distribution function (the probit link). Parameters are estimated by maximum likelihood. The model persists through statistical software implementations (R's glm family=binomial(link='probit'), Python's statsmodels Probit, Stata's probit) and its formal statement in econometric and biostatistical textbooks. [formal: probit-model | substrate: mind | horizon: a life | explicit: yes | epoch: 0.45]
Accepted ontology entry
probit-model
A probit-model is a regression technique for binary dependent variables where the latent variable y* is modeled as a linear combination of predictors (y* = Xβ + ε) with ε ~ N(0,1), and the observed binary outcome y equals 1 when y* > 0 and…
Definition
Why it is in scope
A statistical model for binary outcome data that uses the cumulative distribution function of the standard normal distribution as its link function, built for parameter estimation and hypothesis testing in regression contexts.
Names and aliases
- probit-modelen · CANONICAL
Relations from this entry
- cmsdgh1bw03wc3vv3vx55n190DERIVED_FROM →
Probit model is formulated using the cumulative distribution function of the standard normal distribution as its link function; its definition and operation are a direct derivation from normal distribution theory. Direction: probit-model derived from normal distribution.
- cmsdai2d503n23vv3e00xn5baINSTANCE_OF →
Probit model is a specific kind of regression model for binary outcomes — a generalized linear model with probit link function. A competent speaker calls a probit model 'a type of regression.' Nearest kind: regression (not a leap — regression is the direct parent category for model families like linear, logistic, and probit).
- cmru5nrqe003sr671qxjyxhiqINSTANCE_OF →
Probit model is a specific kind of statistical model used for binary outcome prediction. A competent speaker calls a probit model a type of model. Nearest kind: model (not a leap — model is the direct parent category).
- cmsdgh1bw03wc3vv3vx55n190DEPENDS_ON →
The probit model is defined by using the cumulative distribution function of the standard normal distribution as its link function. The removal test passes: without the normal distribution, the probit model cannot be defined or operate — the entire model is built on the normal distribution's properties. Direction: probit-model depends on normal distribution.
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Record identity
- Created
- Sep 2, 2026, 7:21 PM UTC
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- cd1424aa1a50254e937b70f86489f304eb1b4c63dc3249ca76da47cbf9ac2404