Tagged Questions

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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2
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1answer
27 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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0answers
5 views
0
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0answers
27 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 ...
1
vote
1answer
27 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
votes
1answer
20 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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0answers
55 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 $$\Pr(Y_{ij} = 1 \mid \lambda_{i}) = \Phi(\lambda_{ij}), \qquad [Y_{ij} \perp Y_{ij'} \mid \lambda_i]$$ ...
0
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0answers
58 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
votes
1answer
61 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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0answers
22 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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0answers
35 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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0answers
23 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 ...
0
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0answers
9 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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0answers
17 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 ...
2
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0answers
40 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 ...
0
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0answers
40 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 ...
2
votes
0answers
56 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 ...
1
vote
1answer
174 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 ...
0
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0answers
29 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 ...
0
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0answers
19 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
votes
1answer
86 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 ...
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0answers
56 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, ...
0
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0answers
79 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
votes
1answer
97 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 ...
3
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0answers
42 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) + ...
2
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2answers
65 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 = ...
1
vote
1answer
195 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 ...
0
votes
1answer
64 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 ...
0
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2answers
68 views

IV Probit in R?

Stata has the very useful command ivprobit. For example: ...
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0answers
42 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 ...
1
vote
1answer
64 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) ...
1
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1answer
96 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 ...
0
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0answers
76 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 ...
4
votes
1answer
672 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
votes
1answer
167 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 ...
0
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0answers
24 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
votes
1answer
101 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 ...
0
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0answers
16 views

Do I need to do log transformations for probit?

I am doing a (Heckman) probit. Some of my variables (e.g. N of employees, sales) are highly skewed (skew>2000). Do I need to take log-transformation to make them closer to normal? Thanks!
2
votes
2answers
467 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 ...
3
votes
1answer
120 views

Optimizing False Negative Rate after Logistic Regression

I created a probit model and tested it against a random sub sample of my dataset. I am interested specifically in seeing how many data points I can predict to be FALSE without having too many that are ...
0
votes
1answer
95 views

Normality test of latent residuals (Heckman) Probit?

I am running a Heckman Probit. Both steps assume normal errors of the latent variable, correct? My data is from a survey and a lot of variables are strongly skewed, so I am worried whether this ...
1
vote
1answer
158 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 ...
0
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0answers
42 views

probit model - marginal effects: all zero

To start with, I am a total layman. I've estimated a probit model using GRETL. All marginal effects are 0 (not very small or anything - but zero). I've used some probit and logit models before and it ...
1
vote
1answer
100 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 ...
1
vote
3answers
1k 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
votes
1answer
106 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 ...
0
votes
1answer
597 views

What is the difference between dprobit and probit in stata?

My boss gave me this do file but I have never worked with dprobit. I also need to interpret it, this is the result: ...
1
vote
1answer
44 views

Wald $\chi^2$ value for a probit model

I have fit a probit model in R. However, in addition to the $z$- and $p$-values, I would like to know the Wald $\chi^2$ values for the individual explanatory variables. How do I obtain / calculate the ...
4
votes
1answer
257 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? Many thanks in advance
2
votes
1answer
162 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 ...
2
votes
1answer
103 views

Average partial effects

I need to explain what average partial effects (APEs) are to a very general non-statistical audience (i.e. the APEs derived from a probit model). I have tried to define APEs using layman's terms but I ...