# Questions tagged [probit]

This refers generally to statistical procedures that utilize the probit function. The primary example of which is probit regression where the probit transformation of the parameter p of a binary response distribution is used as a link.

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### Difference between logit and probit models

What is the difference between Logit and Probit model? I'm more interested here in knowing when to use logistic regression, and when to use Probit. If there is any literature which defines it using ...
2k views

### Comparison of log-likelihood of two non-nested models

I know I can only use the log-likelihoods of two models as selection criterion if they are nested. However, I don't understand this completely. Why isn't it possible to apply this reasoning to non-...
14k views

### How to test for simultaneous equality of choosen coefficients in logit or probit model?

How to test for simultaneous equality of choosen coefficients in logit or probit model ? What is the standard approach and what is the state of art approach ?
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### Probit two-stage least squares (2SLS)

I was told that it's possible to run a two-stage IV regression where the first stage is a probit and the second stage is an OLS. Is it possible to use 2SLS if the first stage is a probit but the ...
23k views

### Marginal effect of Probit and Logit model

Can anyone explain how to compute the marginal effect of Probit and Logit model in layman's terms? I am new to statistics and I am confused about these two models.
7k views

### Binary Models (Probit and Logit) with a Logarithmic Offset

Does anyone have a derivation of how an offset works in binary models like probit and logit? In my problem, the follow-up window can vary in length. Suppose patients get a prophylactic shot as ...
5k views

### Linear mixed effect model vs. Ordered Probit vs. Ordered Logit with ordinal response

I have a set of data with an ordinal response ranging from 1-5 (worst to best) and a categorical predictor with five unordered levels. The experiment is a language ...
2k views

### Latent variable interpretation of generalized linear models (GLMs)

Short version: We know that logistic regression and probit regression can be interpreted as involving a continuous latent variable that gets discretized according to some fixed threshold prior to ...
16k views

### How does “stepwise regression” work?

I used the following R code to fit a probit model: ...
2k views

### Alternatives to the multinomial logit model

I am trying to estimate a model of occupational choice with three choices. Are there any alternatives to using the multinomial logistic regression when handling such unordered categorical outcomes? ...
16k views

### How to validate a Multinomial Logit and Probit Model fit?

I would like to know how do you determine the performance of your models. That is, if you fit a multinomial logit or probit model for un-ordered discrete choice. What do you use to evaluate whether ...
17k views

### How to choose between logit, probit or linear probability model?

To decide whether to use logit, probit or a linear probability model I compared the marginal effects of the logit/probit models to the coefficients of the variables in the linear probability model. ...
12k views

### Consistency of 2SLS with Binary endogenous variable

I have read that 2SLS estimator is still consistent even with binary endogenous variable (http://www.stata.com/statalist/archive/2004-07/msg00699.html). In the first stage, a probit treatment model ...
4k views

### 2SLS but second stage Probit

I am trying to use instrumental variables analysis to infer causality with observational data. I have come across a two-stage least squares (2SLS) regression which is likely to address the ...
2k views

### Assumptions of the Ordered Probit model

What are the assumptions of an ordered probit model that must be met? What are the tests to check these?
693 views

### Clarifications about probit and logit models

I know that there is a very good explanation of the technical differences of probit and logit model in this question. However, I would appreciate some common sense clarifications which can be very ...
3k views

### IIA assumption: difference logit and probit

Considering the following question about the Independence of Irrelevant Alternatives assumption: Alternatives to multinomial logistic regression It seems as if IIA is only a problem when using a ...
1k views

### Can logistic regression estimates suffering from subsample abuse be salvaged?

Suppose we have some logistic regression modelling problem; $f(X) = Y$, where $Y$ is binary and $X$ is a vector of normally distributed variables. In industry it is sometimes the case that ...
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### Probit ordered model for non-normal distribution of outcomes

I have the following Y outcomes distribution with the normal density function represented by the superimposed red line: I need to develop a regression methodology to predict $Y$ given a number of ...
2k views

### Why are the fitted probabilities for the linear probability model and the probit model identical?

I estimated a linear probability model (LPM) $P(y=1|x_1) = b_0 +b_1x_1 + u$ and a probit model $P(y=1|x_1) = \Phi(b_0 +b_1x_1 + u)$, where $\Phi()$ denotes the cumulative normal distribution. The ...
1k views

### Comparing two logit or probit curves using a single parameter

I've conducted a psychological experiment on the same subject, under two different condition. For each condition I've collected the number of correct and wrong answer for each stimulus (number of ...
415 views

### OLS and Probit Model regarding a dummy variable being dropped

I've been trying to run a regression using a probit model, but I keep getting a dummy variable being dropped from the regression (in Stata's output) because it predicts the success perfectly. The OLS ...
376 views

### Linear probability model

Is there any advantage or any situation when the Linear probability model is superior than Logit model and Probit model, apart from its simplicity.
2k views

### How to write a logit and probit regression equation?

I have the following linear equation: Dummy dependent variable = dummy main independent variable + control variable 1, absolute value of changes (also between 0 and 1) + control variable 2, sigma (...