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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Is it useful to implement clustered SE in the probit-type models?

For my research, I am implementing a two-stage Heckman procedure. I am working with panel data, so I was wondering if it is common and actually needed to use clustered standard errors for the first ...
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21 views

Robustness check for cross-sectional data by merging data sets and creating year dummy variable

I am currently working on the effects of maternal education on child mortality with cross-sectional data. I got data sets for 2008, 2010 and 2014. I am thinking of doing a robustness checks and I ...
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fmm, lcprob(m): regress y x

I am wondering if someone would help me to understand the the stata command posted here: https://www.stata.com/stata-news/news32-4/spotlight-fmm/ the article explains that the command fmm 2, lcprob(...
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How to use gsem when the independent variables are binary?

According to this website, "Binary—probit, logit, complementary log-log". But does the "binary" here mean independent variable or the latent variable (that is determined by the ...
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How do I interpret xtprobit with random effects?

My probit model has panel data. The dependent variable is a binary outcome that survives = 1 and not survives = 0. I am estimating South Africa's export trade relationships that are importer-product ...
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How do I interpret the results from xtprobit random effects model with robust standard errors in stata?

My probit model has panel data. The dependent variable is a binary outcome that survives = 1 and not survives = 0. I am estimating South Africa's export trade relationships that are import-product ...
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18 views

How do I fix the problem of collinearity, i think i am in the dummy variable trap [duplicate]

I am estimating the whether floods affect electoral outcomes and I am using a difference-in-difference estimator. I have run my probit model with reelected party as the dependent variable (1 if ...
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Obtaining odds ratios from probit (or multinomial probit)

I have an option to run a multinomial logit or probit model on two outcomes (response and remission) to assess treatment effect (T=1 or T=0 is placebo). Any patient with remission also has response, ...
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Is it possible (and even correct) to calculate a confidence interval from an interpolated value?

I am using a probit model to calculate the limit of detection of a diagnostic test. For this, in R, I used glm(): ...
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43 views

Conley Standard Errors in Logit and Probit

I am looking for an implementation of Conley (1999, 2008) standard errors in logit and probit regressions. There is code targeting OLS regressions (1, 2, 3, 4), but I did not find anything adequate ...
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Logit vs probit model [duplicate]

I am planning to do a study that uses binary dependent variable, such as a person is either in the labour force or not in the labour force. The function will have independent variables, for example ...
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Classification of logit and probit models

Savolainen et al. (2011) has a review of discrete choice models used in accident analysis. The paper offers a classification of these models (see image), but some models (e.g. 'Partial proportional ...
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Logit First-stage and Logit Second-Stage in Experiment with 2 binary Instrumental Variables

We are heavily discussing how to analyze our experiment. There is a binary treatment and a binary dependent variable. Therefore I think I should not use OLS but rather probit/logistic regression. It ...
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Comparing prediction intervals to find probability of outcome

I had a thought I was curious about. I was reading some of the other posts, but they didn't answer the question specifically. Say I have a regression y = X'B ~ N(mu,sigma2) From this regression, I ...
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Probits used in LD_50 is the same as the Wikipedia's probit definition? [duplicate]

During my searches I've come to a strange position; The Probit definition in Wikipedia is simple; $$\operatorname{probit}(p) = \sqrt{2}\,\operatorname{erf}^{-1}(2p-1)$$ Then, I've come to a source ...
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Hazard-ratio of marginal effects?

I am doing a study on manipulated hospital discharges using a similar methodology as this paper. In short, we observe that patients are more likely to be discharged directly after a higher tariff rate ...
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Relationship between dependant and independent variables

I'm completing an assignment that asked me to run some probit regression on some variables, and asked bunch of supporting questions. I am struggling to interpret one of them, it asks to "have a ...
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why is the standard error so high for my probit model [closed]

I have created two probit models, and even though p values are significant and sample spaces are large- 10000 samples in both- standard errors seem to be about 6.27e. What could be the reason for that?...
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high standard error for probit model [duplicate]

I have created two probit models with a sample size of 10000 in both. However, when I print the summary of these models, the standard error seems extremely high, 6.29e. What could be the reason for ...
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Difference of the indices i and j in binary response models

I am currently trying to get the hang of binary probit and logit models as well as multinomial models, but I struggle to see the difference in the indices i and j respectively the difference in their ...
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Distributions other than $N(0, 1)$ for the probit-style regression link function

When we do a probit regression, we use the distribution of a standard normal to convert from the linear combination of the predictors to a probability value. Why stop at the standard normal? Why not ...
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25 views

Which test to run … probit or logistic?

IV's: categorical School, categorical Grade Level, categorical Living Arrangement, categorical Race, categorical Illness, continuous Time. DV: withdrawn status (withdrawn or not withdrawn) I want to ...
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Decomposing a probit/logit regression

In an econometric work, I want to assess the causal effect of n variables on a binary character variable y, while I highly suspect that the relation between one of these regressors, say x (which is ...
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Ways to shrink standard errors in models for discrete dependent variables

Consider a simple Probit model $$ Y_i=1\{X_i\beta+\epsilon_i\geq 0\} $$ where $\epsilon_i$ is standard normal independent of $X_i$. (1) Cardinality of the support of $X_i$ Is it true that (and, if yes,...
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Testing equality of coefficients from two probit regressions

I need to test the equality of coefficients from two different regressions (PROBIT). So, I performed two times the same regression (containing multiple independent variables). The only difference is ...
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Why is my quasibinomial GLM estimator biased - Monte Carlo simulation

I'm playing with some Monte Carlo simulations to get an idea of the properties of some linear and non-linear models. The linear OLS model in my case is specified as: $Y_t = \beta_0 + \beta_1x+ \...
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Multiple choice answers and multivariate probit models

I have a survey dataset in which respondents were asked to choose maximum 3 options out of a list of 10 possible answers. I would like to find out how the likelihood of different options being chosen ...
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132 views

Selection equation in Heckprobit

I am trying to implement heckprobit for my dataset. The one issue I am running into is that the stata does not give estimates of the effect of the endogenous binary regressor on the dependent variable ...
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Constructing aggregated choice model

I am trying to model a situation where passengers make choices in their transportation modes when I know the selection ratio of each modes. My dataset looks like this ...
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2SLS with a boolean regressor

So, I have the following linear model: $$y = \alpha + \beta x + u$$ and $x \in \{0,1\}$, i.e. the variable $x$ is boolean. Moreover $x$ may be endogenous, and I have a set of instrumental variables $\...
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Endogenous Sample Selection and Heckit Correction in relation to Research Question

I am researching the funding amounts of start-ups. I am calculating two models: ...
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After running a probit, how can I generate the margins for the whole distribution?

I'm using Stata. I ran a probit of the form $$ \text{outcome}_i = \beta \ f(\text{income}_i) + \gamma\text{ Controls}_i $$ Where $f(\text{income}_i)$ is a fractional polynomial. I'm interested on the ...
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In probit model, why demeaning the data of a regressor lead to no change in numerical values for estimated coefficients except for the constant?

Supppose I have data $\{Y_i,X_{1i},X_{2i}\}_{i=1}^{n}$ generated by model $Y_i=\mathbf{1}(a+b_1X_{1i}+b_2X_{2i}>e_i)$, where $\mathbf{1}(\cdot)$ is the indicator function. I try to estimate this ...
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Probit Models - Statistical Significance and the Number of Observations

I'm currently completing a series of probit regressions where the dependent variable takes the value 0 or 1 depending on whether a civil war was experienced by that country in that year (panel data) I ...
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A question about normalization in probit model (binary response model with normal error)

Suppose I have data on $\{Y_i,X_{1i},X_{2i}\}_{i=1}^{N}$ and the data generating process is $Y_i=\mathbf{1}(\beta_1X_{1i}+\beta_2X_{2i}>e_i)$, where $e_i\sim N(0,\sigma^2)$. Usually, we do a ...
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Is probit transformation the same as probability integral transform?

The image shows the original marginal data $u$ and $v$ on the left, which has a bounded support, and their probit transformations $r$ and $s$ on the right, which has an unbounded support. The ...
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Formula of a zero-inflated negativ binomial with link to probit

I'm looking for the right notation of the probit linkfunktion in a zero-inflated negative binomial. g is the negative binomial and π the link function. Thank you very much!
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IV changes the sign of exogenous variable

After implementing an IV probit model, the signs of many exogenous covariates' coefficients have been flipped, compared to those in the baseline probit model. These signs are now at odds with the past ...
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39 views

Probit model with Gaussian noise

Assume we have the following model setup $$\Phi^{-1}(D)=\alpha+\beta X+\epsilon$$ where $\epsilon\sim N(0,\sigma^{2})$ and $D_{i}=\{0,1\}$. This implies that $$\text{Pr}(D_{i}=1\,|\,X,\epsilon)=\Phi(\...
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Dummy Y variable and interaction effect

I am working on a project where I am studying the effect of a policy. There are 4 groups of people, male-control, female-control, male-treatment and female-treatment. I want to see if the difference ...
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191 views

Interpret regression output using a likert scale IV (using STATA)

I want to run a regression with an binary DV and a likert scale ( 1=strongly disagree, 2=disagree, 3=agree, 4=strongly agree) IV. I think the right model to use is a probit regression, or what would ...
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Using margins after probit estimation to equal probabilities between almost identical individuals

I'm considering a Probit model for the probability that a student will finish the course based on their hours of study, age, sex, origin, how they passed the previous course and labor market situation ...
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Distinguish between probit/ logit

I often read that: If we believe that the functional form of the dependent variable is a cumulative normal density, we may use probit and if we believe that the dependent variable follows a logistic ...
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Predictive model (binary) doesn't seem to fit my own data

I have tried to create a predictive model based on the probit model (common in my field). The model is given as: $$\operatorname{Prob} = \frac{1}{\sqrt{2\pi}}\int_{-\infty}^{t}\exp\left(-\frac{x^2}{2}...
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All else equal, should an MLE estimation have a lower standard error than OLS?

If I have a model with Y$\in${0,1}, and am estimating y= $\beta$x+$\eta$ My understanding is if I use a probit model say, I am imposing structure on the DGP by assuming Y|x=$\eta$ is distributed ...
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Two stage model where both dependent variables are dichotomous

New here so apologies if I do not explain myself as well as I should. I have survey data of 2 decisions that participants make: the decision to vaccinate themselves (yes/no) and their children (yes/...
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Running a Monte carlo simulation of a probit model on Stata

I am trying to run a MC simulation for a probit model on Stata using existing variables. In all the examples I saw, the authors generate the regressors (generally only one) as well as y* and y=(y*>0) ...
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Probit function, Difference in difference approach, Standard errors in R

I'm a novice R user. I'm dealing with some CPS data to evaluate how labor force participation of single female with children changed in response to some policy implementation. The below is my ...
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Is the random slope for a binary, categorical variable in a mixed model also reported in reference to one of the categories?

I'm wondering if I should be interpreting an estimated random slope for a binary categorical variable in the same way that I should be interpreting it if it were a fixed effect. That is, is it ...
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297 views

Comparison of logit and probit estimations

There are a lot of questions concerning logit and probit relations (led by 20523), but I'm still confused with a seemingly simple issue. On the one hand, often we see that for 'rule-of-thumb' ...

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