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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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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13 views

How do you store marginal effects using margins command in Stata [migrated]

I'm estimating a regular probit model in Stata and using the margins command to calculate the marginal effects. I'm trying to ...
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0answers
18 views

How to estimate probit model with binary endogenous regressor using stata? [migrated]

The theoretical principle behind the estimation is clear to me (as is described on Wooldridge's textbook and some previous threads][1]) [1]: probit two stage least squares. However when I check the ...
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14 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
15 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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36 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
38 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
73 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
56 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): ...
5
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1answer
64 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
175 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
51 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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14 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 ...
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1answer
151 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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31 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
66 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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46 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
48 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
39 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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58 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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99 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. ...
2
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1answer
80 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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25 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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49 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 ...
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31 views

robust standard errors newey-west in probit model

In R there are a way to calculate robust standar error newey when we adjust a linear model, using The function NeweyWest() in the ...
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10 views

How to model my data into a probit

I am beginning my thesis, and I need some advice. I am trying to estimate a probit model. The binary dependent variable is employment status, and the independent variables include network size, age, ...
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28 views

dynamic probit model

I want to know if you can helpme I have a binaray response yt take values 1,0 and a covariate Xt continua and I have to estimate the parameters of the model using maximun likelihood method ...
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50 views

Probit regression in R giving singular Hessian matrix

I am trying to run a probit regression using panel data in R by first computing the log likelihood and then using the optim function to optimize. Scale of ...
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73 views

Probit regression in R using panel data - Do we need to normalize the predictors?

I am trying to run a probit regression using panel data by first computing the log likelihood and then using the optim() function to optimize. I have a couple of ...
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0answers
62 views

Mixture of probits: understanding truncated-based likelihoods

I am trying to implement a mixture model of probits to infer the best decision boundary for every latent subpopulation. When doing Gibbs sampling, we eventually have to compute $P(y^* | w_c)$ where ...
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1answer
263 views

Limited dependent variable → ordered probit model with Stata

I have a dependent variable, credit rating, and it is a limited dependent variable. Independent variables are profitability, firm size, stock return, etc. I was advised to use Stata and run ...
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42 views

Model uniformly distributed response in cumulative link (logit/probit) model

I have an ordered response variable (stated preference from strong dislike to strong like) that is virtually uniformly distributed. I am using package ordinal in R to estimate the probability of an ...
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21 views

Covariance matrix specification in multivariate probit

Im having trouble with a multivariate probit model with partial observability/sample selection (written in GAUSS). In this model there is a probit at each of multiple stages, and only one of the two ...
0
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1answer
227 views

Predicting binary dependent gives non-binary predictions

I am trying to predict the result of an experiment (binary dependent variable) based on a number of continuous independent variables. When I do this using a largish model (9 main effects + 2 factor ...
2
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71 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, ...
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107 views

Is there a Matlab code for the probit random effects model for panel data?

Is there a Matlab code for the probit random effects model for panel data? I observe there are Stata codes(a couple of versions) available but I cannot not find any Matlab codes. I would really ...
0
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1answer
145 views

Convert an interval variable to ordinal in SPSS

I am currently conducting a study on reverse mortgages for my master thesis, and I'd like to convert one interval variable into ordinal in order to run a ordinal probit regression analysis. My ...
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54 views

Is there a nice(r) Taylor expansion of the normal quantile function?

Letting $\Phi$ be the CDF of the standard normal, and $\Phi^{-1}$ be the quantile function of the normal, I am looking for the Taylor series expansion of $$ \Phi^{-1}\left(\Phi\left(x\right) + ...
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2answers
68 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 = ...
2
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1answer
417 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 ...
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1answer
88 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 ...
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2answers
102 views

IV Probit in R?

Stata has the very useful command ivprobit. For example: ...
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56 views

Interpretation of marginal effect of probit model

I am quite new with probit models and I recently asked some questions about one of model. I was wondering of one of you could help in interpreting those results. FYI all dependent variables are ...
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1answer
72 views

High p-values in Probit model

Can someone help me interpret those results? I get very high p-value in my probit model but I do not understand why... Some details about my variables: confucius = dependent (binary 1=yes, 0=no) ...
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1answer
125 views

Correlated Random Effects Probit vs. GEE Population-Averaged Probit

My question relates to recent work on correlated random effects probit models (see these slides from Wooldridge) and comparing them to GEE population averaged probit models: Is one approach better as ...
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106 views

Compare the marginal effect for a dummy variable with a continuous variable from a probit model

I use probit model for one regression which consists one independent dummy variable that captures whether the firm is unionized or not. I also estimate the same probit model instead of consisting ...
5
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1answer
1k views

probit two stage least squares

I was told that it's possible to run a 2 stage iv regression where the first stage is a probit and the second stage is an OLS. Is it possible use 2sls if the first stage is a probit but th second ...
6
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1answer
180 views

Inferring parameters for a regression with features of both multivariate probit and ordinal regression?

I am dealing with data which is generated by a complex process, which I elaborate below; I am trying to answer one or more of the following questions- a) what is the right literature to look for ...
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29 views

Visibly different curves but non significant likelihood ratio test

I have run a series of probit regressions for growth variables across 3 environments. I then graphed the resulting curves as probability density functions (3 curves per graph one for each ...
3
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1answer
130 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 ...