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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Business examples for using Probit versus logit model [duplicate]

If some one has an example business problem where you have used probit instead of logit, please share with me. I am not able to understand the situation when to use probit versus logit model. I have ...
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1answer
25 views

Post-estimation tests for ordinal probit [on hold]

I have performed an ordinal probit model in Stata and have 2 queries: The parallel line assumption test (run by oparallel or ...
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29 views

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 ...
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16 views

Ordinal probit model misses one category of independent variable

I am running an ordinal probit model in STATA. the independent variable is a discrete variable and have 2 options )1,2,3) and so i place a prefix i before it. The results show the parameters for 2 and ...
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1answer
34 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) ...
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1answer
21 views

How to identify a binary model with varying mean and variance

I have the following model, Yi = 1.( Xiβ + εi > 0) where εi~ Ɲ(Ziδ,1). or Yi = 1.( Xiβ + εi > 0) where εi~ Ɲ(0, (µ + Ziδ)2) with a binary model, can i identify β and δ in such a model? How? and ...
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1answer
53 views

Confidence intervals for ordered probit [closed]

I'm attempting to compute confidence intervals for an ordered probit. I am a graduate student and it was suggested as one of the tasks to add to my final paper. I have found a few papers discussing it ...
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1answer
40 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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17 views

Interpretation of multinomial probit using MNP package

I used MNP to analyze the election in 1992 and I want to know the probability that non-partisan voters vote for Bush when the personal economic condition varies and the effect of education is ...
2
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1answer
55 views

2SLS probit vs LPM

I am using 2SLS to estimate the effect of education on the probability that one works. In the first stage I regress education on my instrument and the other exogenous control variables. The same ...
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1answer
16 views

writing ordinal probit model equation

assyme the following function walkabality f(conectivity, gender, age, uni, conectivityuni) where wallkability is a dep ordinal variable (1-3 i.e agree, partially agree, disagree) gender m agem uni are ...
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2answers
30 views

Why is simulation used for probit choice probabilities?

As explained in this answer, the probability of a certain outcome in a Logit model can be written as $$ P=\int_{\varepsilon=-\beta'x}^{\infty} f(\varepsilon)d\varepsilon\\ = 1- F(-\beta'x) = ...
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1answer
110 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 ...
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0answers
16 views

Binary decision, evaluating Bayesian probit regression?

Laplacian logistic regression. I have a training set of data and an evaluation set. The response is binary. I have to verify the models by calculating posterior predictive on the evaluation set. Last ...
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24 views

Relationship between the parameters of the Normal distribution and parameters in the probit with multiple predictors?

According to A. Agresti (2007, p. 73) in binary probit regression: "The parameters of the normal distribution relate to the parameters in the probit by mean (mu = -alpha/beta) and standard deviation ...
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1answer
36 views

Hypothesis of probit model

I would like to know if we need to test the assumption of residuals' normality when we have probit model? And if this assumption is violated how can I correct it with Stata? In the case of Probit ...
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1answer
42 views

Predicted probabilities from probit

Assume following probit model: $y_i$ = $\phi$($\beta_0$+$\beta_1x_1$+$\beta_2x_1^2$+$\beta_3d_1$+$\beta_4d_2$) where $d_1$ and $d_2$ are dummies or in Stata: ...
2
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1answer
69 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 ...
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0answers
34 views

probit consistent estimation

I have a probit model $$Pr(LFP=1) = β_1 + β_2\ln(WW_i) + β_3 KL6_i + β_4 NWIFEINC_i + β_5 WA_i + β_6 WE_i + u_i$$ with $$\ln(WW_i) = α_1 + α_2WE_i + α_3 AX_i + α_4 AX_i^2 + e_i $$ WW is a continuous ...
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1answer
68 views

Generating data from Probit regression, cut off 0 and variance 1 necessary?

I am trying to create a dataset using a Probit regression model in R, where I have an intercept and three covariates. I first fix a set of coefficients for the three covariates, generate these ...
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0answers
24 views

Penalized ML estimation of non-linear probit

I have a model of the form $P(y_i=1) = \Phi(\frac{w_1^{\beta'x_i}-w_2^{\beta'x_i}}{\sigma' x_i})$ where $y_i$ is a binary response, $\Phi$ is the normal CDF, $w_1$ and $w_2$ are non-negative ...
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11 views

interaction term in ordinal probit model

I am working on an ordinal probit model. If i plan to introduce an interaction term between a dummy variable and an ordinal variable (having 3 and in some cases 5 categories) , then is such an ...
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0answers
30 views

Heckman Probit Model the number of explanatory variable in selection model?

I run a Heckman Probit model which is sometimes called as Heckit. It consists two parts like this: |1| Y X1 X2 X3, |2| select(Y2 X1 X2 X3) Y covers Y2 but not vice versa. The question is whether i ...
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1answer
51 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 ...
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1answer
11 views

How to compute the pdf for logit/probit models?

According to the probit/logit models, the change in probability due to a change in an explicative variable x is given by the following equation: P(Y = 1 |X) = ...
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1answer
25 views

Interpretation of Odds in Probit Regression

Logistic regression is concerned about modelling log-odds, i.e. logits. Hence, the odds of the computed probabilities can be interpreted accordingly. However, when estimating a probit model, one could ...
3
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1answer
80 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 ...
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16 views

Is the residual term from probit or logit model orthogonal to $X\beta$?

It is well known fact that for OLS model, $Y=X*\beta+ \epsilon$. $Y$ can be decomposed into two orthogonal components: $X\beta$ and residual term $\epsilon$. The two terms are independent of each ...
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21 views

Which type of model suits the best for my dataset? (y=Binary; x1,x2=Nominal)

My dependent variable is winning (Binary: WIN-1, DRAW/LOSE-0). I classified soccer teams by there post-match data. Therefore, I've got a cluster membership nominal variable for each team (x1) and a ...
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0answers
24 views

Probit regression with misclassified binary dependent variable in R

Is there a generalized linear mixed-effects model implementation for R that could handle misclassified binary data? Unless I have overlooked something in the documentation, glmer with ...
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1answer
39 views

What to do when parallel regression assumption violated

When the dependent variable in a regression model is ordinal, I know that we often use ordered probit/logit to estimate the model. These have an assumption called the parallel regression assumption. ...
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38 views

Fast Algorithm for Bayesian Measurement Model

I want to estimate a Bayesian Measurement model. That is I am concerned with the rating of each judge $j$ of the value of some trait $z$ for each observation $i$. Not all raters will have rated each ...
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1answer
41 views

Probit assumptions of unbiasednes

Can someone tell me what are the assumptions of unbiasednes for simple probit model like this $ Prob(y=1|x) = G^{-1}(\beta_0 + x\beta) $ I know that dependent variable models are estimated by MLE so ...
4
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1answer
126 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 ...
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1answer
125 views

Random-effects probit model

I am currently using a mixed binomial model with the following specification in a paper I recently submitted (using lme4): ...
6
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1answer
203 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 endogeneity ...
5
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1answer
696 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 ...
4
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1answer
79 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 ...
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15 views

Multiple choice models

As it is known, there are logit and probit models based on logistic and normal distribution. Can I build a new same model based on other distibution? For example, it may be double exponentional ...
4
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1answer
176 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). ...
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0answers
56 views

Autoregressive distributed lag (ADL) models and Dummy variables

Is it okay to use an Autoregressive Distributed Lag (ADL) model with a dummy variable as the dependent variable? Or should I use a combination of logit/probit with an ADL model? I realize it might ...
2
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1answer
95 views

Probit or Logit in Generalized Linear Model [duplicate]

I'm trying to apply GLMs on a dataset in which dependent variable Y is dichotomous. I applied either logit and probit models, and probit fitted better than logit model. How do I justify the choice of ...
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60 views

Two-stage probit least squares

I am estimating a two-stage probit least squares (2SPLS) model. From the readings I have done so far, it appears the first stage of the 2SPLS has to be estimated with a probit, and then a continuous ...
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1answer
79 views

GLM link function for bimodal probit fitting?

I am trying to model a set of data I have physical reason to believe can be represented by a bimodal normal cumulative distribution function (Technically it is a bimodal log-normal CDF, but I think I ...
4
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1answer
53 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 ...
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65 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 $$\Pr(Y_{ij} = 1 \mid \lambda_{i}) = \Phi(\lambda_{ij}), \qquad [Y_{ij} \perp Y_{ij'} \mid \lambda_i]$$ ...
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118 views

Statistical Analysis help for thesis - Correlation, Probit, Tobit and Moderation

Hello CrossValidated users! I am writing here cause I need some guidance on my statistical analysis which has turned out far too complex for my basically begineer stats skills and my self research. ...
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1answer
91 views

Estimating standard error in a probit: econometrics or programming problem?

This question has two parts, as I do not understand whether my problem is theoretical (identification of the parameters) or practical (insufficient R skills). Econometrics Most "probit" style ...
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28 views

Probit and probability of being a member of a group

I was wondering if there was a specific way to convert probit regression results into a probability that a test subject is a member of group 1 (vs group 0) if you break up the dependent variable into ...
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60 views

Conjugate Prior for Probit likelihood function

I am trying to do a Bayesian analysis in which my likelihood function is a probit function on two parameters. From various sources, I found out that Normal distribution is a conjugate prior to probit ...