Questions tagged [multinomial-logit]
Multinomial logistic regression models a categorical dependent variable that can take on >2 different levels.
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Is there a way to estimate a binary choice model with constant alternative-specific variables?
I have a relatively basic question.
It is well known that there should be some variability among cases in alternative-specific variables in order to apply conditional logit.
But imagine that we have ...
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Why does estimating $k - 1$ probabilities in multinomial regression is way better than $k$? [duplicate]
I am probably going to ask dumb question, but I think I can't understand the crucial advantage of the multinomial regression compared to just logistic regression. Or is it just generalization of the ...
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Multinomial logistic regression v chi-square
I run an experiment with two treatments. My dependent variable is a categorical variable with three levels - participants choose either no product, product A or product B. What I want to do now is to:
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Multinomial Logit
I'm trying to fit a model with statsmodels, Multinomial Logit Model.
This works fine, but I'm quite unsure if it is the right model for my case and how to treat my independent variables.
So my ...
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How to estimate a nested logit model using mlogit in R in the case of panel data and degenerate branche?
I'm using a Discrete Choice Experiment.
I have 9 choice sets with 3 alternatives (2 alternatives and an opt-out), the alternatives are described with 4 attributes.
I want to use a nested logit model ...
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1answer
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Why is there a difference between chi-square and logistic regression?
I have two categorical variables: gender (male & female) and eye color (blue, brown, & other). And I also have age.
I used the chi-square test and the multinomial logistic regression.
When ...
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25 views
Interpreting results of multinominal logistic regression
I have run a multinominal logistic model with my dependent categorical variable, WINNING_PARTY, taking the following values: gov, corp, org, indiv, univ, or in part....
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How to add Indivivual Specific Variables for unlabelled alternative (using interactions) using mlogit with R?
I’m using DCE with unlabelled alternatives, 9 choice set with 3 alternative each (2 option and Optout alternative), described with 4 attributes.
I've started with a conditional logit (with only ...
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multi class text classification with multiple dependent variable to one set of predictors in r
I am doing multi class classification in text in r on a dataset containing two columns; feedback and topics.
Some feedback has been assigned to more than one topics and some more than two but most of ...
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Contrast coding DV in multinomial regression
In a multinomial logistic regression (for example, with 3 levels of a categorical DV), my understanding is that the DV is essentially dummy-coded, with coefficients corresponding to differences ...
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1answer
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Get equation from glm coefficients: calculate y manually?
I am trying to understand the math behind the glm(). Specifically, how to apply equation based on model predictors to calculate my ...
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nnet::multinom confidence intervals extremely narrow, when mean of independent variable >> variance
I am using the package nnet to fit multinomial regression models using multinom().
When fitting the model using an independent ...
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Significance of fixed effect coefficients in multinomial logistic regression
I am trying to do a multinomial logit regression, and I understand that the fixed effects coefficients are a bit difficult to interpret and that they can in some cases be 0 or negative but actually ...
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Estimating a multinomial logit with random effects in R
I have the following data-structure:
we observe individuals $1...N$ multiple times for a different wheather (can be rainy or sunny). Furthermore we have the age for each individual and the choice he ...
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Interpretation of effects plot in latent class regression
I'm fitting a latent class model with covariates using poLCA in R. It seems to work fine, but I have some trouble understanding ...
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Should I use a GEE model for a mixed logistic regression problem with a multinomial outcome?
I'm trying to model linguistic data where my hypothesis assumes that a multinomial categorical response from a subject is a function of fixed effects (gender and subject's occupation, say) and, since ...
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Literature on multinomial logistic regression with random effects
The title pretty much says it all: I am looking for a good reference to understand multinomial logistic regression with random effects and the estimation of such models. Furthermore, I am also looking ...
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1answer
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Is a multinomial logit model just the maximum of many logit models?
I'm trying to understand how a prediction from a multinomial logit model compares to a prediction from many logit models. A few videos and wikipedia have lead to me to believe that the categorical ...
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Testing for equality in single-response-category proportions in a multinomial sample
Problem:
I have a multinomial variable with three response categories. I am asked to test the effect of certain categorical predictors on the proportion of each category. To my understanding, this ...
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Using multinomial logistic regression to test for heterogeneity
I have been asked to use polychotomous logistic regression to test for heterogeneity or independent variable across multiple outcomes levels, and then change-in-estimate method to identify other ...
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Difference between Mixed Logit model and hierarchical bayesian logit?
I'm studying the discrete choice analysis;
The utility of person $i$ for alternative $k$ is: $$U_{ik} = \beta_kx_{ik} + \epsilon_{ik}$$ where $\beta_k$ is the parameter of interest and with $\...
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1answer
74 views
Stata multinomial logit IIA assumption violated or not?
My dependent variable is Choice, 0 for non-issuers, 1 for seasoned equity issuers, 2 for convertible issuers and 3 for bond issuers.
I use the following command to ...
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Relation between multinomial logit model and multi-class neural network
I'm wondering how much differ in these two kinds of model when comes to predict discrete choice.
Consider a data-set explanatory $\boldsymbol{x}$ and response $\boldsymbol{y}$ where $\boldsymbol{y} \...
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Does Neural Net with Softmax activation function violate the IIA assumption?
Multinomial logistic regression have assume the IIA (independence of irrelevant alternatives (IIA), IIA assumption: difference logit and probit); but I'm wondering if using Neural network in which the ...
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Convexity of Multinomial Logistic Regression
For completely separable training data, is the Multinomial Logistic Regression performance function(Maximum Likelihood) convex?
In general, independent of the separability is the Maximum Likelihood ...
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Failing to recover true parameters in simulations of multinomial logit
I am trying to understand how multinomial logistic regression works. In the first round, I am using the following model representation:
$$
P(Y=k|X_1=x_1,X_2=x_2)=\frac{\exp(\beta_{k0}+\beta_{k1}x_2+\...
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How is multinomial logistic regression separating non-pivot classes?
As far as I have understood multinomial (i.e., more than 2 classes) logistic regression with, let's say, $K$ classes runs $K-1$ independent binary logistic regressions with one class, generally the $K$...
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“Double censored” model?
How would I properly model the following:
A disease has three stages of diagnosis: No symptoms, Mild, Advanced. These are based on behavioral criteria.
There are also brain pathology scales that do ...
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40 views
chi-square when the cells are not independent
Imagine an experimental setup as follows: 30 subjects each make three preference judgements: they choose a color for each button shape. So, the raw subject data could look like:
...
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Regression variables not used/applicable for certain cases [duplicate]
I have a rank-ordered logit model in which the various independent variables are pertinent for some cases but not others. For example, cases 1, 2, 3, & 4 might have variables A & B that are ...
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36 views
power analysis - multinomial logistic regression
How should I conduct a power analysis for a multinomial logistic regression analysis? I see the option in G-power software but I don't know if the default parameters are ok.
I have 1 categorical ...
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15 views
Joint Probability density function for multinomial distribution
I am using the below link to understand the likelihood function in for the multinomial distribution however, the notation of this paper is a abit confusing.
https://czep.net/stat/mlelr.pdf
The ...
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Softmax Linear Regression/ Multinomial Logistic Regression with shared coefficients and different inputs
I am trying to build a Softmax Regression model for 3 classes, where, unlike what is usually done, the coefficients between different options are shared and what varies are the input variables.
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Would binary logistic regression or multinomial logistic regression be more appropriate for this study?
I am doing a study on the financing behaviour of firms and my dependent variables (financing behaviour) will be binary. Eg. firms that sought debt financing = 1 and firms that did not seek debt ...
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192 views
How to interpret coefficients of a multinomial elastic net (glmnet) regression
I'm trying to model a membership in one of three well-being clusters (flourisher, normative, languisher) based on a set of predictors, using elastic net for both variable selection & modelling. I ...
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Incorporating rank-ordered logit results from different samples
I would like to create rank-ordered logit models to predict the outcome (winner in this case) of variants of a multi-player game. For the most part, the predictors for each variant differ. However, in ...
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1answer
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Is it valid to use Anova (in R) to compare alternative multinomial log-linear models?
I am familiar with the idea of comparing alternative linear regression models using anova(model1,model2), for models fitted using ...
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How to interpret multinomial regression results? [duplicate]
I want to investigate the relationship between stock traders' past success rate (i.e. the number of total winning trades divided by the total trades executed) on the status of their current trading ...
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1answer
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Translating multinomial logistic regression into mlogit choice-modelling format
I have an EEG dataset where I have several subjects in multiple sleep stages (~10 subjects, 5 stages). I want to see which of a number of EEG-derived metrics (measured in each subject in each sleep ...
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111 views
Marginal effects in multinomial logit in R
I am trying to calculate average marginal effects (dF/dx) for a multinomial logit model in R. Package mfx provides the solution only for binomial (and not the multinomial) model. Is there a package or ...
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1answer
52 views
Approach to Analyzing Semi-Rare Events
I am often faced with analyzing data that follow a pattern as shown in a mock example in the image below. Key data characteristics:
for any value of the predictor (e.g. temperature), the most ...
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Sampling bias in multinomial logistic regression
I am interested in estimating a set of coefficients in a multinomial logistic model. However, I only observe a subsample of the true sample in which base category $A$ was chosen. I have no way of ...
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93 views
Interpretation of marginal effects multinomial logit R
I'm not really sure how to interpret marginal effects when calculated with mlogit and effects function from R
Here is the code
...
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27 views
What is difference between logit model and multinomial regression model for discrete choice?
I am confused in discrete choice models! Which one is better and why?
Multinomial regression is very different than logit model based on result and formula. Which one is better? Multinomial and nested ...
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1answer
50 views
Repeated measure for multinomial logistic GLMMs in SPSS?
I am analyzing some linguistic data, where each subject has to rate the acceptability of a number of sentences on a scale of 1-7. I am running a Generalized Linear Mixed Model in SPSS, with a ...
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1answer
45 views
Are there any examples of multinomial or logistic regression as an outcome model using propensity score weighting?
I apologize if this is an inappropriate question, but does anyone have more recent texts on implementing some type of covariate balance weighting scheme (entropy balancing, IPTW, etc) where the ...
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26 views
Is there a standard approach for estimating robust multinomial logit models?
I have been reading the "Robust Statistics" book by Morona, Martin and Yohai. To estimate a robust version of logistic regression, they recommend using redescending weighted $M$-estimator. For more ...
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Can I use categorical predicting variables with command estsimp in package Clarify?
I was hoping to use the package Clarify (Tomz, Wittenberg and King) to present results from a multinomial logistic regression model, but received an error notification at the very start: "factor-...
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Logistic regression of both ordinal response and explanatory variables [duplicate]
Here the last column is my response variable. I have four predictors that are ordinal. How best to code them to preserve their "ordinal" properties?
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Identification issues with alternative specific constants in multinomial logit
Suppose an individual $i$'s utility from alternative $j$ is given by:
$U_{ij} = \alpha_j +v_j'\omega+\epsilon_{ij}$
where the joint density of $\epsilon_{i}$ is type 1 extreme value.
The choice ...
