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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18 views

simulation of an item response theory 2PL model [closed]

I would like to simulate a 2PL probit model. I want to set up some arbitrary item parameters $a=(a_1,...,a_J)$, $b=(b_1,...,b_J)$ and abilities $\theta=(\theta_1,...,\theta_I)$ ($J$ number of items ...
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20 views

Signs of MarginalEffects and CoefficientEstimates in Multivariate Probit

Could someone explain that the sign of coefficient estimates and their corresponding marginal effects in the Multivariate Probit Model is the same or they could be different? IF they are different, ...
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23 views

Sensitivity Testing - Using Probit GLM to Infer Parameters of the Independent Variable

I am an engineer working with some sensitivity data. In this type of experiment, you test a device at a certain stimulus and observe whether or not it fails (binary outcome). For example, you might ...
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14 views

Bad controls, Probit, and prediction

I have three related questions: For causal inference, does a variable that is an outcome of the variable of interest also need to be confounded with the outcome variable for it to be a bad control? ...
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15 views

understanding R2 in probit

I try to create a model to predict football (socker) results with a performance variable. It doesn't really matter how this performance is calculated since any performance variable is an adequote ...
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21 views

Probit Regression and Reverse Causality

In the context of my Master's Thesis, I am using cross-sectional data to investigate the impact of digitalisation and it's various tools on the propensity to adopt various sustainable behaviours for ...
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20 views

How to interpret marginal effects when both DV and IVs are in fractional form?

I ran a fractional probit model in which both IV and DV are in fractional form (i.e. proportions). Now I am having difficulty in interpreting the marginal effects (dydx). Suppose, the variable "...
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15 views

Which model is the most appropriate for my data?

I've been searching for the right model for several months, but i ended up with nothing untill now. That's why i'm here asking for help. My research purpose is to analyse the impact of rural programs ...
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19 views

Calculating the effect of trustworthiness on obtaining bank loan and on loan rate (interpretation question)

I am reading a paper that discusses how people's perception of borrower's trustworthiness affects his/her probability of loan approval, and also loan rate. This is from a RFS paper on page 2474 (2.1) (...
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22 views

Correlation in the Bivariate probit regression?

Could you explain to me how to interpret the coefficients Rho and athrho in the bivariate probit regression. In my case the athRho is significantly different from zero (0.399), does this mean that the ...
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44 views

Probit model with error term

I'm writing a probit model but I don't know if the error term is written correctly. I wrote my model like this: $$\Pr(Y_i=1|X_i)=Φ(x'_i\beta) + ν_i$$ where $v_i$ is the error term. Is this correct?
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55 views

95% Confidence interval for extrapolated value from linear regression?

I'm writing a program to estimate the lower limit of detection for a nucleic acid assay. A typical analysis will have 5 concentrations with 10 independent replicates each, the dependent variable being ...
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Heteroscedasticity in categorial/binary data

I fitted a probit model in R using the glm function where my dependent variable is a binary variable and my indepentent variables are also binary and categorial variables. I also fitted a ...
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How do I determine the effect of a variable on whether a user will become a paying member

I'm trying to figure out whether taking more lessons has an effect on a user becoming a paying member. Imagine I have the following dataset, for thousands of users over a few months. I'm trying to ...
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55 views

Calculating confidence intervals for a linear regression/probit model

I've written a program to calculate the lower limit of detection for a nucleic acid test (qRT-PCR). The program takes the raw data (a set of replicates of the same input concentration [10 x 1 copy/ml, ...
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51 views

Chamberlain’s random effect probit model

Why is Chamberlain’s random effect probit model referred to as a random effect model, even though the idea behind such a model is to introduce a correlation between the unobserved heterogeneity term, ...
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Analysing dose-response relationship when my data does not adhere to sigmodial relationship

I have been trying to analyse the chronic toxicity data to my Bachelor's dissertation in R. The problem is that the data does not adhere to a sigmodial relationship when trying to calculate the LC50 ...
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Making comparisons between percentage point and percentage

I am currently using a probit models to estimate the effects of maternal education on child mortality. I got results in terms of percentage points, ie mothers with education are less likely to ...
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Problem producing Confidence Interval and got an NaNS when using probit analysis

I have a dose/response relationship from the chronic toxicity test I have done and I intended to use a probit analysis (LC_probit function of the ecotox package) to calculate the LC50 value of the ...
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25 views

glm.fit: fitted probabilities numerically 0 or 1 occurred [duplicate]

Probit <- glm(lfprt ~ expr + educ + age, data = data, family = binomial(link = "probit"), control = list(maxit = 50)) Keep getting an error, don't ...
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10 views

Generalized chain rule for the multivariate probit model

I am struggling with understanding the generalized chain rule for the multivariate probit model. Suppose I want to take the derivative of the multivariate probit model w.r.t. one of the coefficients, ...
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37 views

Probit with fixed effects

Could anyone elaborate on why fixed effects (or within estimator) will not work in the probit setting? Thanks in advance.
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60 views

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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65 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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49 views

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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40 views

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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184 views

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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81 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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28 views

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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32 views

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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53 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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35 views

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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93 views

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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25 views

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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32 views

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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26 views

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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60 views

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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13 views

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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25 views

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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12 views

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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1answer
32 views

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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94 views

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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18 views

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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110 views

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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9 views

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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1answer
289 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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