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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10answers
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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 ...
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1answer
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-...
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3answers
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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 ?
14
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2answers
22k views

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 ...
12
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3answers
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.
13
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2answers
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 ...
5
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1answer
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 ...
22
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1answer
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 ...
11
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2answers
16k views

How does “stepwise regression” work?

I used the following R code to fit a probit model: ...
8
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3answers
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? ...
4
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3answers
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 ...
2
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1answer
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. ...
10
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1answer
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 ...
16
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1answer
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 ...
8
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2answers
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?
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1answer
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 ...
5
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1answer
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 ...
4
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1answer
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 ...
2
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1answer
2k views

How to do simulation of Probit link?

How do you solve the following problem? A Simulation Study (Probit Regression). Assume $y|x\sim {\rm Binary}(p)$, where $p= E(y|x)$, and $Φ^{-1}(\pi)=-1+5.1x_{1i}-0.3x_{2i}$ Generate data with $x_{1i}...
2
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2answers
2k views

Graphing and Analyzing Probit Regression

I am currently analyzing a data set having to do with oak tree mortality. I am trying to understand the correlation between dead crowns (dead = 0, live = ...
5
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1answer
2k views

How to estimate a bivariate probit (biprobit) model in R with a different set of explanatory variables? [closed]

I'm trying to estimate a bivariate probit model (also called biprobit model) in R where the set of explanatory variables is different for both binary outcomes. Thus, my setting is: \begin{align} Y_1^*...
3
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1answer
525 views

monotonic transformation, probit vs logit

In my firm I am developing a model using a probit model. I noticed that when benchmarking with a logit specification, the logit slightly improves the model goodness-of-fit. Talking with a colleague ...
2
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1answer
880 views

How to use multinomial probit coefficients to predict?

I fitted a multinomial probit model with one independent categorical variable Y (levels 1,2,3) and two explanatory variables X1 and X2. Using mlogit package in R like this: ...
2
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1answer
623 views

Understanding Maximum Likelihood Estimation (MLE) and its confidence intervals

I'm trying to figure out if I am actually understanding MLE correctly, or at least applying it correctly to my data. My data consists of several patients for which I have some data, which is used in ...
2
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1answer
2k views

interpreting the coefficient on a logged independent variable from a probit model

I am using a double model with log transformed independent variables and have calculated average partial effects. Now I am now not sure how to interpret the coefficients; particularly those from the ...
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1answer
644 views

Scale parameter

I came across the scale parameter used in the logit and probit models. Does any one know what that is and what it is used for? What would go wrong if I did not use it?
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1answer
2k views

Heckman sample selection

On page 9 in http://jenni.uchicago.edu/Oxford2005/four_param_all_2005-08-07_csh.pdf ATE - the average treatment effect is the expected gain from participation in a program for a random individual. For ...
6
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1answer
499 views

non-classical measurement error in a binary outcome model

I have a binary outcome model that I am estimating with a probit, so $$\Pr(Y=1\vert x,z)=\Phi(\alpha +\beta\cdot x^* + z'\gamma)$$ I am interested in the marginal effect of $x^*$ on $\Pr(Y=1\vert x,...
3
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2answers
1k views

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 ...
3
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1answer
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 ...
3
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1answer
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 ...
2
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0answers
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 ...
2
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1answer
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.
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1answer
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 (...
0
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1answer
117 views

Interpretation of interaction term in a probit estimation

I know this question may be duplicate but I don't find any answer that I could understand. I am running panel probit estimations. Estimations include interaction terms that I am able to interpret. ...
0
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1answer
826 views

Heckman/Two part model with endogenous binary variables

I have a model with the continous variable(Y) that takes zero values. So, I am trying to use the limited dependent variable model (Two part/Heckman) , but I have binary endogeneous variables (two) ($...