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Questions tagged [logit]

A name given to the log-odds function, which maps probabilities to the real line.

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Interpretation of logit model without reference category

I have developed a logit model with binary dependent variable in R using the glm function. Overall, the independent variables include seven nominal, 23 ordinal, and two numeric variables. The nominal ...
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1answer
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Adjusted R Square For Binomial [duplicate]

mtcars=data.frame(mtcars) m=glm(vs~mpg+cyl+disp+hp+drat,family="binomial",data=mtcars) m=glm(vs~wt,family="binomial",data=mtcars) I seek to estimate pseudo-r-...
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Can some one explains me how to use logit regression with multiple categorical independent variables in eviews?

I want to perform logistic regression(logit) on my data. My dependent variable is a binary value. My independent variables are a couple of categorical variables and some continuous variables. I want ...
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1answer
13 views

the constant coefficients are penalized in the ridge logit conditional model?

I am estimating a conditional ridge logit model, there is very little bibliography about it, and I do not know if the constant coefficients are penalized. My model has 2 variables and 3 alternatives, ...
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33 views

Can a linear and logit model have the same shape?

While I was working on an exercise based this book, I discovered something interesting. When I fit a logit and simple linear probability model on the data (see code below), the predictions are almost ...
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1answer
69 views

Conditions in which the sign of a coefficient will change between a linear probability model and a logistic model

I am estimating a model where the DV is a binary variable and the key independent variable is the interaction between a dummy variable and a continuous variable. I am getting an very odd result where ...
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2answers
27 views

How to simulate, if a customer will buy

If customer 1 will buy a product with a probability of 0.6 and every following customer 0.7, how can I simulate a system with n customers? The result should show which customers bought and which ...
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12 views

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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23 views

Logit regression: Treat binary indepedent variables as continuous or as categorical for the marginal effect?

I have two logit models: A standard binary one (y=0/1) and an ordered logit model (y = yes, definitely/yes, maybe/no, probably not/no, definitely not. Now, to get the marginal effects of the binary ...
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1answer
26 views

Re-calibrating Intercept on logistic regression models for unbalance data

I have data-set that I’m modelling using logistic regression as land.cover~H1+H2+H3+H4+H6+H8+H14. My response and categorical variables are binary. However the number of 0 and 1 in my response ...
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Understanding logits for Binary Classification using XGboost

I am having a hard time understanding the results of my machine learning model for a binary classification task. Basically, I am using a library called SHAP to interpret the results of my models. The ...
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choice of the lambda parameter in the logit multinomial ridge model

I can not find clear literature on how to choose the penalty parameter in the logit multinomial ridge model. As read in the linear models and trying to adapt it to the model I need it would be through ...
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Binomial GLM: is it valid to use proportion for the endogenous variable, without weighting based on number of trials?

I am struggling with something that seems like it should be relatively straight forward, but my searches thus far have not yielded results. Earlier guidance on the site suggests that when using a ...
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nested logit: must all nests contain at least 2 items?

I'm estimating a model about how people travel in R. There are 4 alternatives: air, car, bus, and train. I want to create a nested logit model in which travelers first choose whether or not to fly, ...
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3answers
37 views

Comparing two logit models

Folks, Would appreciate any advice on the following topic. My question I would like to answer is the following. What are the determinants of being a First Time Buyer of a House? Based on a survey ...
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What regression model should I use for this problem?

I am a lowly undergrad working on a research project with my university. I have only a basic grasp on regression analysis so please bear with me! We are seeking to find consumers' willingness to pay ...
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21 views

Can I use logistic regression to calculate the optimal classification threshold between two class based on a single contiguous variable

I have a single contiguous variable, x, and there is two possible classes/labels y for n observations. I need to build a simple binary classifier with a threshold on x so that the number of ...
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1answer
49 views

Is it possible to compare probabilities of 2 logistic different models with same data set? [closed]

I have two logistic regression models (A&B), one gives probability of "person A" buying "Product X" and other model gives probability of person A buying "product Y". The training data for both ...
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1answer
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Changes in significance and effect size (though constant SEs) when controlling for a categorical variable. Correlation test & interpretation?

I am interested in the effect of the extend to which an occupation consists of routine codifiable tasks and individual job displacement. I have individual level survey data and use a logistic model to ...
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Given a simple logit panel data model, the MLE estimators are inconsistent

Consider a binary choice model, $P \left( y _ { i t } = 1 | x _ { i t } , \alpha _ { i } \right) = F \left( x _ { i t } \beta _ { 0 } + \alpha _ { i } \right)$, $$F ( z ) = \frac { e ^ { z } } { 1 + e ...
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19 views

Missing one category while predicting with polr

I am trying to predict football outcome using an ordered logit model and I am using R. I used polr in R and everything works fine until the prediction part. the dependent variable is the result (home ...
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Have I understood logictic regression output correctly? Logit, odds ratio and probability ratio

Here is an example model using diamonds dataset: ...
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340 views

StatsModel Logistic Regression

I am running a fairly simple Logistic Regression model y= (1[Positive Savings] ,0]) X = (1[Treated Group],0) I got a coefficient of Treated -.64 and OR of .52. My question is how to interpret the ...
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Ordered logit with different choice sets at different times

I have the following dataset: at time $t_1$, a person faces the following ordered choice set $y \in [0,1]$, and at time $t_2$, he faces the ordered choice set $y \in [0,1,2]$. Assume the utility is $...
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Can I add a constant and then transform my explanatory variable? [duplicate]

My current model is of the form $$\log(\frac{y_i}{1-y_i}) = \beta_0 + \beta_1 x_1+\beta_2 x_2.$$ Is it okay if I consider the model $$\log(\frac{y_i}{1-y_i}) = \beta_0 + \beta_1 x_1+\beta_2 \log(x_2+1)...
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Understanding Multivariate Logistic Normal pdf

I'm trying to understand the Multivariate Logistic Normal distribution, in order to plot its pdf and compare it with a Dirichlet distribution. I believe I can follow the pdf derivation for the ...
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The link between logistic regression and logistic sigmoid

My professor once stated that the logistic sigmoid function is the inverse link function to logistic regression. I cannot find mathematical deductions showing this. Can anyone confirm his statement ...
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20 views

How to calculate the probabilities and log-likelihood of the conditional logit model?

I need to estimate the coefficients of the computational output that the "mlogit" package gives me. I follow the steps to estimate the coefficients that vary by individual and alternative given in ...
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1answer
49 views

Conditional logit or multinomial logit?

I have the following problem I need to use a discrete choice model to determine the time values (VOT) of 3 transport alternatives (car, bus and train). Looking at the literature of the discrete choice ...
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1answer
62 views

Is there a connection between the normal and the logistic distribution?

Regarding Bayesian statistics I found in a script that there is such link, and the logistic arises in context of a normal distribution and a "binary state". However, I have no idea what is the meaning ...
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21 views

estimation conditional logit

I'm creating a code to estimate a conditional logit model. Comparing with the code that I adjust with the package "mlogit" I get very different coefficients, could you help me determine where I'm ...
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1answer
44 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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Combining Results of Simulation Replications (Random-Intercept Logit Models under Confounding)

I've written some simulation code in R to learn about the behavior of a random-intercepts logit model under varying degrees of confounding. The simulated scenario is three points in time, two groups, ...
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Applying logit model on another data set

I have a following situation: I am testing a probability of harvesting in one forest - no previous harvesting data available. I have found an article about harvesting model - logit model done in a ...
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2answers
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How to create a logistic regression model based on a two way table

question Given a table such as : $$ \begin{array}{ll|ll} & A & {} \\ & & 0 & 1 \\ \hline B& 1 & 44 & 27 \\ &0 & 443 & 95 \end{array} $$ If I ...
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Pooling Horse Racing Odds with a Logit Model

I am using a logit model to pool the odds from two bookies and a betting exchange. I have thousands of data points across many races, horses and race tracks and am trying to predict the probability of ...
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1answer
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How to interpret the marginal effect of a dummy regressors in a logit model

I have a problem interpreting the marginal effect of a dummy variable in a logit model. (I am using Stata to estimate the logit regression) I've run a simple logit say this: ...
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1answer
57 views

How to calculate the probability for this multinomial logit model?

In multinomial logit models, the probability of the observed choice ranked 1st among all option is given by this formula: p(choice = j) = exp(x_j*b)/(\sum(x_i*b)) ...
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Validation of logit model

I have performed econometric analysis with binary logit model using national representative survey (weighted) data for a given country. I then received a suggestion that no tests or robustness ...
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R: Interpreting bayesian model averaging of multinomial logit

I am having troubles interpreting results from a BMA of a multinomial logit. THE SETUP My goal is to analyze how companies choose a payment method in M&A based on the acquirer's financial ...
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Discussion of Robustness

I have to include a discussion of robustness in my report. What are ways to discuss the robustness of my models? I run several logit models. But I don't know how to include something about the ...
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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
57 views

GLM and implementation of Poisson regression model in R by hand

first of, this is not my school exercise but a given example that I'd like to convert from Stan to my own code. I am very much a pragmatic learner so doing this helps me a lot to visualize the problem....
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1answer
86 views

Interpretation of different logistic regression models to test hypotheses

I would like to test two hypotheses, but I am a little bit confused. I have a binary dependent variable z, my key variable a is ...
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0answers
35 views

Discrete-time survival model as linear probability model

Discrete-time survival (event history) models are typically estimated using a nonlinear transformation such as logit, probit, or completementary log-log. Logit assumes proportional odds, and similarly ...
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1answer
32 views

Combing logit and linear regression

I am looking for a proper method for my research. I want to analyze left-right political position of a person. My idea is to combine logit regression with a linear regression. Logit will decide on ...
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1answer
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Why is it easier, and just as valid, to assess overlap with logit propensities?

I'm looking for an intuitive explanation of why the logit transformation gives us a better picture of the overlap in the distributions:
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102 views

When is logit function preferred over sigmoid?

I found out that logit and sigmoid functions are inverse of one another, and are used in binary classification, but is there a preference of one over another in any circumstances, or can they be used ...
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1answer
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Adjusted odds ratio question

I have a question about adjusted odds ratios for matched data. Let's assume that we have a binary variable that we want to determine the odds ratios for (let's say smoking or not smoking, this is the ...