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
309k views

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

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 ...
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 ...
14
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3answers
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 ?
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 ...
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 ...
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.
11
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2answers
16k views

How does “stepwise regression” work?

I used the following R code to fit a probit 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 ...
10
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1answer
427 views

Deriving likelihood function for IV-probit

So I have a binary model where $y_1^*$ is the latent unobserved variable and $y_1 \in \{0,1\}$ the observed. $y_2$ determines $y_1$ and $z_2$ is thus my instrument. So in short the model is. \...
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2answers
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Derivation of confidence and prediction intervals of predictions for probit and logit (and GLMs in general)

The derivation of the prediction interval for the linear model is quite simple: Obtaining a formula for prediction limits in a linear model . How to derive the confidence and prediction intervals for ...
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4answers
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Does non-stationarity in logit/probit matter?

I would like to ask - I am using logit to investigate, if some variables improve the risk of currency crises. I have yearly data from 1980 for lots of countries (unbalanced panel), dummy variable is 1 ...
8
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2answers
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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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3answers
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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? ...
8
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1answer
4k views

Choose best model between logit, probit and nls

I'm analyzing a certain dataset, and I need to understand how to choose the best model that fits my data. I'm using R. An example of data I have is the following: ...
7
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2answers
4k views

Estimate multinomial probit model with mlogit (R package)

From the document and help, probit model is supported by mlogit. But when I tried it with these R scripts, the estimation takes much longer time to run (than the logit verion) and the result is quite ...
7
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1answer
246 views

Identifiability in generalized linear random effect model?

Suppose I observe binary $Y_{ij}$ for $i = 1, ..., N$ and $j = 1, ..., J$ and I want to model $$\Pr(Y_{ij} = 1 \mid \lambda_{i}) = \Phi(\lambda_{ij}), \qquad [Y_{ij} \perp Y_{ij'} \mid \lambda_i]$$ ...
7
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0answers
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Inverse Mills ratio after OLS

Short version of the question: Is it possible to create a dependent variable in the first step of the Heckman Selection model such that it is possible to obtain the values for the calculation of the ...
6
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3answers
1k views

Which logit or probit model should I use for multiple response / dependent variables?

I have $300$ time series objects that constitute the $300$ columns of matrix $X$. This matrix has $5$ rows and represents $5$ days of time series information for each $300$ columns. I set up a $300\...
6
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1answer
1k views

Using predicted probabilities as regressors

I am working on a project where I investigate growth in wages due to migration. I correct for the endogeneity in the decision to migrate (only those that are most likely to gain from migration will ...
6
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1answer
3k views

Why Bayesian logistic (probit) regression instead of standard logistic (probit) regression?

I wonder under what condition I should use Bayesian logistic regression instead of standard logistic regression, or vice verse? I have individual-level data regarding whether a person purchase a ...
6
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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 ...
6
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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,...
6
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0answers
658 views

Average Structural Function Calculation

EDIT: I have solved this problem myself. The problem with the simulation below is that the omitted variable should not be included in the 'true model'. I have written a blog post with a more detailed ...
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 ...
5
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2answers
9k views

2SLS - logit/probit in the second stage?

I just have a quick question: what if I'm interested in estimating a logit/probit model in the second stage, can I follow this two-step procedure by running OLS in the first stage (endogenous variable ...
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 ...
5
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1answer
833 views

Do you include a reference category for a series of dummy variables in a probit regression?

Do you include a reference category for a series of dummy variables in a probit regression? If so, how would you interpret the reference category? The question underlying my confusion is that I don't ...
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^*...
5
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1answer
1k views

Interaction effects in non-linear models

I have a general question about interpreting interaction effects in a non-linear model. I understand the reasons Ai and Norton (2004) suggest using the stata inteff command to help interpret ...
5
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1answer
494 views

Null hypothesis of probit model Wald test

Say I estimate the following probit model: $$ins = \Phi(\alpha + \beta_1 age + \beta_2 educ + \beta_3 hg + \beta_4chronic + \beta_5 hisp + \beta_6 lin) + u$$ where: $ins = 1$ for any individual who ...
5
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1answer
2k views

How to interpret log-transformed predictors in probit regression?

I am running a probit model with several continous and one log-transformed predictor (firm size as total assets). I am unsure how to interpret the coefficient of -0.341 on that variable. I used the ...
5
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1answer
317 views

Regression model for road accidents data

I want to model road accidents data to identify 1) the major causes of accidents and 2) predictors that can explain the accident severity measured by the passengers injury level (minor, major, fatal). ...
5
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2answers
2k views

Simultaneous Equation System for logit/probit?

Is it possible have an SES where the component equations are probabilistic, say, logit or probit? I am evaluating a number of quality metrics of services provided by a number of providers. The metrics ...
5
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0answers
515 views

Intuitive explanation of “integrate out random effect”

We are trying to figure out an intuitive reasoning behind integrate out the unobserved random effect. The specific formula is: $f\big(y_i|x_i;\beta, \sigma_c\big)=\int_{-\infty}^{+\infty}\Big(\prod_{...
4
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2answers
1k views

Calculation of log-logit or log-probit models according to Finney using R

I'm trying to implement the logit/probit model derivation as introduced by Finney using sample data from http://dge.stanford.edu/SCOPE/SCOPE_12/SCOPE_12.html, chapter 6 (this links to a pdf), page 130,...
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 ...
4
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1answer
36 views

Simulate probit model using values of the latent variable

I am trying to simulate a probit model using a latent variable Z of the following form: \begin{aligned} y_{i} & = \begin{cases} 1 & \; \text{if } z_{i} > 0\\ 0 & \; \text{if } ...
4
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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-...
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 ...
4
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1answer
532 views

Interaction term

I wanted to ask about interaction term. I am having an ordinal probit model. The two of the independent variables that i have are discrete 1-Uni( a 0,1 dummy variable) and second is continuity (1,2,3) ...
4
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3answers
5k views

Marginal effect of squared variable in Probit Model

I want to estimate the following probit model $employed_t=\beta_1 age + \beta_2 age^2$ and I use the Stata code probit employed c.age##c.age Using the command <...
4
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1answer
550 views

Probit: Stata log likelihood iteration 0

When working with probit models in stata the first line of the output is (for a sample of 583 with 3 variables): Iteration 0: log likelihood = -400.01203 If I understand this correctly the ...
4
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1answer
961 views

Maximum number of alternatives in a discrete choice model

We are modeling a discrete choice scenario, with alternative-specific coefficients. We also break the assumption of independence of irrelevant alternatives. To model this, we are using an alternative-...
4
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1answer
1k views

Ordered Probit and categorical variables

I wanted to run a quick and easy (or so I thought) regression on some data I have but now I am starting to doubt whether or not the regression makes any sense. I have seen some similar questions but ...
4
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1answer
1k views

Convert probit regression coefficient into correlation

Most coefficients (e.g., odd ratios, mean differences, etc.) can be converted into a (Pearson-like) correlation coefficient. Q: Is there a conversion from probit coefficient --> correlation ...
4
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1answer
263 views

Where is penalized probit regression?

I am trying to fit penalized model for binary outcome with few events and correlated covariates. Probit and logistic regression models are among the most widely used models for binary outcome. I am ...
4
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1answer
212 views

Steps of multinomial probit estimation

Does anybody have any source containing explanation of steps in estimating coefficients of multinomial probit model (from likelihood function to first and second derivatives)? Thanks in advance. EDIT:...
4
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2answers
1k views

Multivariate ordered logit or probit [closed]

I have two ordinal dependent variables, each having three response levels. You can use an ordered logit or probit model for such data if you have one dependent variable. I've seen some papers about ...

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