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.
1
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3answers
67 views
How to test for simultaneous equality of choosen coefficients in logit or probit model?
How to test for simultaneous equality of choosen coefficients in logit or probit model ? What is the standard approach and what is the state of art approach ?
1
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0answers
29 views
Estimate multinomial probit model with mlogit (R package)
From the document and help, probit model is supported by mlogit. But when I tried it with these R scripts, the estimation takes much longer time to run (than the logit verion) and the result is quite ...
0
votes
0answers
28 views
Running a Probit on Survival-Time Data?
Can I run a probit on survival time data? It's discrete-round, and I want to look at whether lagged variables affect the failure event. I am, however, getting negative coefficients for a probit ...
2
votes
1answer
86 views
Comparing two logit or probit curves using a single parameter
I've conducted a psychological experiment on the same subject, under two different condition. For each condition I've collected the number of correct and wrong answer for each stimulus (number of ...
1
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0answers
74 views
bivariate probit with endogenous covariate testing
I am interested in learning more about testing for the bivariate probit model with an endogenous treatment regressor. I have figured some stuff out -- summary below, since I don't see much on this ...
2
votes
1answer
62 views
Simulating ordinal variables using fitted probit models
I have fitted a probit model for an ordinal response and a number of predictors, using polr function in R. Now I want to use this fitted model in order to sample from the conditional distribution of ...
0
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0answers
47 views
Gibbs sampling for the latent variables in Sample Selected Probit
Consider the following model of data generation:
$\ y_1 = I(y_1^*>0) \ where\ y_1^* = \beta_1X_1+\epsilon_1 $
$\ y_2 = I(y_2^*>0)*y_1 \ where\ y_2^* = \beta_2X_2+\epsilon_2 $
$\ y_3 = ...
1
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1answer
89 views
Estimating parameters for probit multiplied by something
Assume you have a model of the form $y = x_1\Phi(\beta_0 + \beta_2x_2 +\ldots+ \beta_nx_n)+u$ where $y_i\in(0,x_{1i}]$ and $\Phi$ is the probit function.
How can we estimate $\beta$s in e.g. Stata?
-4
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1answer
92 views
Probit analysis shows no significant variables
In my probit output all p values are insignificant. I want at least some of my variables to be significant. How I correct it?
My variables are: crossbreed, age2, gender, education experience2, ...
0
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0answers
103 views
probit tobit model
I am using a dataset with approx 2000 obs to look at the effect of a number of covariates on:
whether a person is unemployed or not (binary)
the period of time a person has been unemployed (Q ...
0
votes
1answer
51 views
Finding choice probabilities by using utility with logit and probit models
I am using a formula to calculate the utility, which is as follows:
v_{ij} = 1 - x*beta + delta_i + e_{ij}
delta_i ~ N(0,phi^2)
e_ij ~ N(0,sigma^2)
v_{ij} is ...
0
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0answers
24 views
Gibbs Sampling weight more recent samples heavier?
I'm implementing an online Albert and Chib Gibbs sampler for Probit regression (see http://www.cs.ubc.ca/~emtiyaz/Writings/EMTstatisticalcomputation.pdf or ...
0
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1answer
55 views
Scale parameter
I came across the scale parameter used in the logit and probit models. Does any one know what that is and what it is used for? What would go wrong if I did not use it?
1
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1answer
123 views
Exploratory data analysis for discrete data
I am using a probit and a logit model for obtaining the choice probabilities of some data. What kind of plots can be useful to conduct a exploratory data analysis for these data?
Here is the ...
0
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0answers
71 views
Ordered Probit/Logit with random coefficients
I searched everywhere but I didn't find what I want, that is why I as the question here. Does anybody know of a function in R which allows to estimate ordered ...
1
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0answers
48 views
Logit versus Probit [duplicate]
Possible Duplicate:
Difference between logit and probit models
I have data in which the response variable is binary. So, I fitted logit and probit models and obtained the results. How can I ...
0
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0answers
39 views
0
votes
1answer
114 views
Panel data analysis with ordered probit model
I have a panel dataset of survey responses collected by the world bank in Egypt in 2004, 2006, and 2008. I want to run an ordered probit model to test the impact of firm characteristics on their ...
0
votes
0answers
47 views
Interpretation of Expression in ordinal regression
Suppose we are looking at an ordinal variable with $4$ categories. So there are three threshold coefficients $b_1, \dots b_3$ and one probit slope $b_4$. What is the interpretation of the following ...
0
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2answers
200 views
Coefficients in ordered probit model
Suppose I have $4$ ordinal variables and a single covariate ($\log_{10}(x)$). When I run an ordinal probit model, I get three threshold coefficients and one probit slope. Call the threshold ...
0
votes
0answers
61 views
MLE and ordinal probit regression
Suppose we have a data set $X$. This data set consists of ordinal data (4 levels). To get estimates of the threshold coefficients and probit slope ($\beta_1, \dots, \beta_3$ and $\beta_4$ ...
1
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0answers
67 views
Individual-level parameter estimates from ordered choice regressions
I have got a question regarding ordered choice regressions in R.
I have several demographic variables with which I want to explain the ordered choice of individuals within a survey in an ordered ...
0
votes
1answer
185 views
Probit model marginal effects
p<-glm(GRADE~GPA+TUCE+PSI,family="binomial"(link="probit")); summary(p)
is the probit model
...
0
votes
0answers
79 views
Rjags Error: Adaptation incomplete
I am running bivariate probit model under the Bayesian approach. For your convenience I have attached my R codes. I have three random effects, Ur, ...
1
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0answers
67 views
Is there a better alternative to a logit / probit regression when all dependent variables are dichotomous?
I'm working on a clinical trial dataset with binary response. All dependent variables are also binary. My first impulse was to simply run a standard logit/probit regression and be done with it. But ...
1
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0answers
877 views
Inverse Mills ratio after OLS
tl;dr:
Is it possible to create a dependent variable in the first step of the Heckman Selection model such that it is possible to obtain the values for the calculation of the Inverse Mills Ratio for ...
6
votes
3answers
333 views
Which logit/probit model do I use for multiple reponse/dependent variables?
I have $300$ time series objects that constitute the $300$ columns of matrix $X$. This matrix has $5$ rows and represents $5$ days of time series information for each $300$ columns.
I set up a ...
1
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0answers
80 views
Report coefficients or odds ratio in ordinal logit/probit?
I'm doing ordinal logit/probit only to analyse the direction of causality (e.g. if some variable makes it more likely to observe a low scale or a high scale). No interpretation is needed beyond this.
...
3
votes
1answer
590 views
Negative coefficient in ordered logistic regression
Suppose we have the ordinal response $y:\{Bad,Neutral,Good\} \rightarrow \{1,2,3\}$ and a set of variables $X:=[x_1,x_2,x_3]$ that we think will explain $y$. We then do an ordered logistic regression ...
5
votes
1answer
126 views
Do you include a reference category for a series of dummy variables in a probit regression?
Do you include a reference category for a series of dummy variables in a probit regression? If so, how would you interpret the reference category?
The question underlying my confusion is that I don't ...
1
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1answer
134 views
Probit analysis using 13 cases and checking normal distribution
Can I use probit if my dependent variable has data that looks something like this, 1 case is equal to 0, and 12 cases are equal to 1?
Thanks
3
votes
1answer
93 views
Combining two survey samples
I have two surveys of business owners. One is a sample (sample 1) of business owners who were not members of the association, done using a random digit dialing approach. The other is a sample ...
1
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0answers
157 views
Separation of multiple overlapping normal distributions
The problem is separation of multiple normal distributions of fish length, each normal distribution representing a distinct year class contributing to the overall population in a long-lived species. ...
5
votes
0answers
135 views
Average Structural Function Calculation
EDIT: I have solved this problem myself. The problem with the simulation below is that the omitted variable should not be included in the 'true model'. I have written a blog post with a more detailed ...
8
votes
1answer
324 views
Choose best model between logit, probit and nls
I'm analyzing a certain dataset, and I need to understand how to choose the best model that fits my data. I'm using R.
An example of data I have is the following:
...
2
votes
1answer
145 views
Logistic regression across groups
When running a logit/probit model for particular sets of outcomes on a set of participants (whether they did a certain behavior at least two times), how can one best control for differences when the ...
3
votes
0answers
191 views
Multivariate ordered logit or probit
I have two ordinal dependent variables, each having three response levels. You can use an ordered logit or probit model for such data if you have one dependent variable. I've seen some papers about ...
1
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0answers
168 views
Multinomial probit for varying choice set
I apologize in advance for the "how do I run this model in R" question, but it turns out that's the shape my problem has assumed :-). Hopefully I have enough substantive questions surrounding it to ...
2
votes
0answers
202 views
ordered probit in JAGS
I am running into an error
Error in node Y1[5]
Observed node inconsistent with unobserved parents at initialization
trying the following bugs model in JAGS ...
2
votes
3answers
149 views
“Incorrect” p-value during probit regression when probability of a response is zero
I am running a probit regression with glm. I got a non-significant value (p~0.98) for an interaction that other statistical methods suggested should be significant. Looking into it, I think it's ...
1
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1answer
168 views
Probit ordered model for non-normal distribution of outcomes
I have the following Y outcomes distribution with the normal density function represented by the superimposed red line:
I need to develop a regression methodology to predict $Y$ given a number of ...
4
votes
1answer
688 views
Probit estimation - insignificant coefficients with a significant difference
I'm a postgraduate economics student but not of the statistically inclined sort :)
Im running a regression to estimate the likelihood of a patent being litigated. I have two dummies for the patent ...
3
votes
2answers
138 views
How to explore/model this problem?
I have data extracted from a state machine. Each row of data looks like this:
label1,label2,label3,impedance,did_state_change
The column data types are described ...
37
votes
5answers
14k views
Difference between logit and probit models
Can anybody please tell me the difference between the logit and the probit model? I'm more interested here in knowing when to use logistic regression, and when to use probit. If there's any literature ...
3
votes
1answer
348 views
Convert probit regression coefficient into correlation
Most coefficients (e.g., odd ratios, mean differences, etc.) can be converted into a (Pearson-like) correlation coefficient.
Q: Is there a conversion from probit coefficient --> correlation ...
3
votes
3answers
2k views
Marginal effect of Probit and Logit model
Can anyone explain how to compute the marginal effect of Probit and Logit model in layman's terms?
I am new to statistics and I am confused about these two models.
2
votes
2answers
5k views
Interpreting probit results in Stata
I have read the Stata manual but I am still having trouble understanding how to interpret these results. I am looking to determine how each parameter affects the outcome given a 1-unit change.
The ...
1
vote
0answers
95 views
Likelihood function for a multiperiod probit with autoregressive latent variable
I'd like to evaluate the likelihood function of a multperiod ordered probit model with an autoregressive random component, but i am having trouble arriving at the likelihood function.
As an example ...
1
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1answer
494 views
1
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1answer
426 views
Time dummies in ordered probit regression
I am trying to interpret the coefficients on the year dummies in an ordered probit regression. My data is a panel with 20 years. I have included 19 year dummies with the exclusion of the first year. ...
