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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questions
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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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1answer
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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25 views
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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9 views
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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1answer
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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12 views
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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6 views
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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8 views
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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1answer
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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1answer
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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1answer
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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1answer
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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1answer
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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36 views
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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0answers
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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1answer
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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28 views
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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1answer
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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19 views
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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0answers
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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1answer
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 ...
2
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1answer
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 ...
