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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Adapting weights for a glm() binomial regression
I've been facing a common problem. I can't use my dataset’s weights to estimate a binomial family model. I've been using the glm() function to estimate a probit model, but when my weights variable is ...
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Centering covariates and factors in probit model to interpret coefficients
This is my first post ever here so apologies if I missed any of the guidelines, or if the question is off base.
I am trying to interpret regression coefficients of a probit model for both continuous ...
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How to formalize this problem for a ML solution ? “closeness” of local min/maxes of two variables
i am mostly self taught so apologies in advance if my formulation is different to what is commonly used among trained ML pros.
I have two variables X(t) and Y(t) what I wanna know is whether the ...
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Confused about motivation for variable selection - probit model
I am running a probit regression which aims to determine which variables influence whether a graduate feels 'mismatched' (e.g. not using the qualification they've learned) in their job.
We are using ...
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Strangely identical Probit and IVProbit results
I'm currently running 3 probit regressions, each of which have IV variants. In each model the regressors and instruments are identical (the coding essentially looks exactly the same for each model, ...
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2answers
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Probit with variance not equal to 1
In probit models the latent variable is assumed to be of the form: $y=\alpha+\beta x+\epsilon$ with $\epsilon \sim N(0,1)$.
What if instead $\epsilon \sim N(0,\sigma^2)$?
Is there a way to estimate $...
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1answer
29 views
Why margins and mfx yield different results in R?
When I run a simple logit regression between a binary variable $y$ over another binary variable $x$, the average marginal effects obtained by the function logitmfx (...
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Calculating pseudo-$R^2$ for out-of-sample probit model forecasts
I'm trying to replicate parts of:
Estrella, A., & Mishkin, F. S. (1998). Predicting U.S. Recessions: Financial Variables as Leading Indicators. Review of Economics and Statistics, 80(1), 45–61.
...
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25 views
Comparison between Logit and Probit models [duplicate]
I'm new in econometrics and I'm working in a probabilistic model and using Stata for this, but when I was going to compare the Logit and Probit I did not know which one win in this case, because there ...
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28 views
help determining ROPE for bayesian multilevel probit model
I am having difficulty determining a justifiable region of practical equivalence (ROPE) for a parameter from a multilevel probit model
Below is the posterior distribution for the fixed-effect of ...
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15 views
How to test for sample selection bias in heckit estimation?
I'm doing a heckit two step estimation by hand where i first estimate the labor force participation, compute the inverse mills ratio by using the linear predictors of the model and add it as an ...
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1answer
38 views
Sample selection bias and logistic regression
I am struggling with possible sample selection bias at the moment, and I was wondering whether someone has a methodological tip or possibly knows of fancy statistical/econometric tools I could use to ...
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Binary Dependent Variable Regression
I'm struggling with part (b) of the above question. If I use the probit model, then $P(Y_i|X_i=x,W_i=w,A_i=a)=\Phi(\beta_0+\beta_1x+\beta_2w+\beta_3a)$. Not sure how to proceed with the variance ...
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1answer
40 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.
...
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Categorical variable postestimation at cluster level
I have a question about categorical variable regression and post-estimation procedures.
My aim is to estimate the “probability of success” (say, odds-ratio) at an aggregate level using a lower-level ...
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1answer
449 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^*...
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Probit model- pseudo R2
I am working with a probit model where my depended variable is whether has private loans(yes=1 no=0), while my independent variables are age, educational level, marital status, number of household ...
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Missing Data for Binary Dependent Variable
I have a Binary dependent variable (0/1) with panel data of three years(1 2 3). I want to measure the determinants of a woman choosing abortion using ordinary probit or logit. The problem is that no ...
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How does d-prime calculation relate to binomial mixed models with probit link?
for a study I tested participants in a same-different task (1AFC) about melodies. There were 3 versions of each melody (within-subjects factor "version").
So d-prime seems the natural response/...
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How to estimate the MLE for a probit panel data model in R? [closed]
Can you recommend a good package in R to calculate the MLE for a simple panel data probit model?
I would like to use GHK simulator to do it. But What I found is not for panel data in R.
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1answer
33 views
What model to use [closed]
I have data on whether an audition was successful or not and some data that could help explain the success/failure up to some extent (I have about 10 categorical variables and 2 continuous).
So the ...
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1answer
46 views
How can I regress if all the variables are categorical?
I am working with a dataset of 335 categorical variables. The dependent variable is also categorical variable, as following:
How satisfied are you with your life: 1.unhappy ... to 10. very happy.
I ...
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Probit Hypothesis Test: $H_0: \beta_1 \geq 1$
Problem
Given the output of a probit model and no knowledge of the sample data:
...
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Can anyone explain the case of the probit model where we can identify the variance of the error term?
I was told that the variance of the error can be identified in a probit model in a specific case, and cannot find anything about it online.
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1answer
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Comparing coefficients of two different probit models---is this “bad statistics”?
Apologies for any stupid mistakes, or if the answer to this question is trivial: I have no formal statistical training. Long story short: can we meaningfully compare coefficients of two different ...
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Difference in Coefficient Interpretations of Linear Probability, Logit MFX, and Probit MFX Models
I have been trying to make sense of what the difference in a LPM, Logit Marginal Effects, and Probit Marginal Effects models would be.
For instance, say I ran $employment = \beta_0+\beta_1edu+\dots+...
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1answer
83 views
Estimating elasticity using different regression models
My question is how to estimate elasticity based on a Probit model. I know the following formulas are used to estimate elasticity based on OLS (1) and logit (2) models (Ewing & Cervero, 2001):
(1)...
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1answer
159 views
Interpretation of variable in a probit model
I am struggling interpreting the coefficient of a variable which is expressed as a proportion in a probit model. As it currently stands , I am interpreting the average partial effects of this variable ...
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1answer
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Interpreting regression results for different units of measure
Could you kindly help me with interpreting the results from the Probit model for different units of measure of the covariates?
Consider the Probit Model
$$
Y=1\{X\beta+\epsilon \geq 0\}
$$
with $\...
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1answer
68 views
How to deal with missingness of dependent variable in unbalanced probit model
I am trying to estimate a probit model on the probability of suicide over the next year in a population. Unfortunately for this research, suicide rates are very very low so the probability of suicide ...
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1answer
253 views
In R, How can I calculate the elasticity of Y with respect to X, when Y is binary?
I have a dataset that I am doing in R and I need to calculate elasticities in it. To simplify my model, I have Y = XB + u, and I need to find the elasticity of Y with respect to X.
My investigation ...
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Bivariate probit with a fixed rho [closed]
In a series of papers by Altonji, Elder and Taber -- for example 1 -- they check the robustness of bivariate binary choice models by seeing what values of $\rho$ (the correlation coefficient between ...
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1answer
81 views
Compare link function: generalized linear mixed binomial
How does one compare the Goodness of Fit for different models of some given binomial data using Generalized Linear Mixed Models.
Specifically we want to know whether a model with a logit link gives a ...
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1answer
355 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 ...
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Probit model specification
im writing a paper that involves using a probit regression, would this be a correct summary of what a probt model is and how it works?:
"the probit specification is a binary-dependent model that ...
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1answer
45 views
Using probit regression coefficients to derive probabilities? [closed]
I'm reading a paper here that uses a Probit Regression. I'm not entirely familiar with how this works. But, I'm wondering if there's a way to use the coefficients from Table 3 to derive the ...
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Is the decision surface for a Probit model linear?
For example, if we threshold our classification on $0.5$, is the decision surface necessarily linear? It is linear for Multinomial Logit models, but it's not obvious to me that it is for Probit ...
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1answer
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OLS and Probit possible on large sample enough?
I think I understood that normality of residuals may not be a problem if the sample is large enough (cf, here).
My question is: Would my sample be large enough to be analysed using a probit and an ...
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1answer
139 views
Pseudo R2 and prob>chi2
I am running a profit regression and I am finding difficulties in interpreting the prob>chi2 =0.0000 statistic. Also, should I be concerned that Pseudo R2=0.0209? How do I interpret it.
Thank you.
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Bivariate probit : is there a heteroscedastic version of the model?
I know there exists a version of the simple probit model which is robust to heteroscedasticity (the heteroscedastic probit model). Is there an equivalent for the bivariate probit model? Is there a way ...
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1answer
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R/Stata Can I include a categorical variable in a Logistic regression when one of its values perfectly predicts one of the outcomes?
Suppose I have the following data
df = data.table('y'= c(1,1,1,1,1,1,1,0,0,0,0), 'x' = c(1,1,1,1,1,1,1,1,1,0,0))
where x = 0 perfectly predicts y = 0. I ...
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Is a binary probit model which predicts the outcome of every observation to be true still useful for analysing effects of explanatory variables?
So I have a binary probit model for labour participation restricted to a specific age group and region. The remaining explanatory variables include sex, education, and having dependent children (all ...
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1answer
162 views
Difference between probit of log(x) and probit using inverse lognormal cdf of x
Topic: probit and logprobit regression.
Context: I have to implement a model of size at maturity in a wild population and I must choose a binomial linear model to estimate the parameters based on ...
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2answers
86 views
What can you infer about the effects of explanatory variables in a binary probit model?
Obviously in linear regression, the coefficient tells you whether the effect of a change in an explanatory variable on the response variable is positive or negative and how much a change of one unit ...
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1answer
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Which p-value should I use ? (Probit and interaction terms)
I ran a Probit model to determine which variables/interaction terms are significant. I got these results:
Probit: "mino" is not significant.
Whith the margins command (Averadge marginal effect) I ...
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1answer
242 views
How to calculate probit marginal effects over groups with Stata [closed]
How to properly calculate marginal effects of a probit model to capture marginal effect of one variable over a group. The setup is the following (simplified version):
Data:
...
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1answer
145 views
Is there heteroskedasticity in binomial GLMs?
We know a linear probability model (LPM) will produce heteroskedastic errors by definition because of how the variance of a bernoulli r.v. is defined. My question is whether the same is true for logit/...
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test the significance of the marginal effects of a spatial probit model
I'm using the CRAN package spatialprobit to estimate a Spatial Probit. The function sarprobit calculates the marginal effects ...
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Are there problems with estimating regressions of longitudinal data by year?
I am studying the behavior of 900 firms for a period of 10 years. The data is a balanced panel. Multivariate analysis consists of Tobit estimations for each year and probit estimations for each year. ...
