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Questions tagged [multinomial-logit]

Multinomial logistic regression models a categorical dependent variable that can take on >2 different levels.

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Calculating risk from multinomial logistic regression and competing risks

I’m interested in predicting certain events an entity can experience. With logistic regression I would estimate the risk of a single event using p= exp(ß0 + ß1*x1 + ... + ßk*xk)/(1+exp(ß0 + ß1*x1 + ......
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Multinomial Logistic Regression: small groups

I am implementing a Multinomial Logistic Regression, but I am encountering the possible issue of having very small groups when I create a frequency table of the dependent variable Y and one of the ...
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Multinomial logit with ridge penalization and value of time

I am fitting a multinomial logit model with ridge penalty and in turn estimating the value of time (VOT) or availability to pay (WTP). I want to work with real and simulated data. For the real data I ...
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What's the equivalent function for mLogit() if random effects are involved? [duplicate]

mLogit is the function for running multinomial logistic regression in R. What if we have random effects (mixed-effects model), what's the adequate function (and ...
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Delta Method Average Marginal Effects Multinomial Logit

Following the incredible demonstration in Statalist by Jeff Pitblado on how to calculate - using the Delta Method - the Standard Errors for Average Marginal Effects of a Logit Model. Q: What would ...
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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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Logistic regression when the number of options differs by group?

I have data from a laboratory experiment in which I look at the effect of expanding the choice set on a particular option being chosen. The idea is that introducing an Option "B" reduces demand for an ...
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Interpretation of a classic multinomial logit vs. BMA of multinomial logit

EDIT #1 Most likely I have set up the function bic.mlogit in a wrong way. @Jesper Hybel, hopefully, directed me in the right way. With the new setup I get two sets ...
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How to calculate the multinomial logistic regression's intercept and coefficients manually?

I have a trouble on calculating the multinomial logistic regression's intercept and coefficients manually. Although I managed to get the coefficients from SPSS but I don't understand how to get them ...
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Simulate clustering in multinomial logistic regression

I want to simulate a multinomial logistic regression dataset. Suppose you have 1000 data points, the first 60% belong to the reference group 1, the next 30% belong to group 2 and the remaining 10% ...
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Marginal effects in Multinomial logistic regression & Multinomial probit regression

I am trying to calculate the marginal effects of a multinomial logistic regression. To do this I use the mlogit package and the effects() function. Here is the codes I have run: Creating reference ...
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The marginals of the nested logit are identical?

Consider three random variables $\epsilon_0, \epsilon_1,\epsilon_2$ and suppose that their joint CDF is $$ F(\epsilon_0, \epsilon_1,\epsilon_2)\equiv \exp\Bigg[-\exp(-\epsilon_0)- \bigg[\exp\Big(-\...
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Estimation Multinomial Logit [closed]

I need to create a code manually corresponding to the likelihood of the multinomial logit model in R. I have not been able to get the same results from some packages (mlogit, multinom). My database ...
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Simulate/Generate Data for Multinomial Logistic regression

How to simulate data for Multinomial Logistic regression? For Example i want to generate a high dimensional data set with 90 subjects and 500 independent predictors. The ratio of Classes should given ...
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DV is customer bank choice

DV is Customer bank choice that is categorical with 5 response variable, like CBE,AIB,COOP,OIB,AB banks customers selected as sample thus i need to use multinomial regression, but i am not clear with ...
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Using multinomial logistic regression to make predictions [closed]

I have run a multinomial logistic model in SAS with 5 independant variables and I need to use the results from this model to make forecasts of use of care. I have used the predicted probabilities from ...
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Choice modelling with context

We are trying to model itinerary choice for an airline. Given the attributes of a number of itineraries, we try to say the probability of booking for each one. Context matters here because the ...
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Stated Preference and Socioeconomic Data

I am conducting a survey which includes a stated choice experiment and socioeconomic-related questions. In the stated preference experiment, each respondent faces 3 scenarios. And, I am trying to ...
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Backward elimination in a multinomial logistic regression model?

Following this UCLA article, I have fit a multinomial logistic regression model in R (say that Group is a factor with levels ...
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Multinomial Logit with different choice set for each individual

I am currently trying to model a discrete choice problem using multinomial logit. The issue is that each individual faces a "different" choice set. In Stage 1 an individual is told that he can ...
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Fitting a Multinomial Logistic Regression model with binary, categorical and continuous predictor variables

I am trying to find out how my dependent variable is influenced by the independent variables. My outcome variable can assume three categories: P(positive), D(doubt) and N(negative). 6 of my predictor ...
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Most appropriate statistical test for multiple comparisons with categorical response variable in r

I am looking to compare the call type usage of humpback whales across three different group compositions. There are 13 different call types, and I would like to develop a model that will allow me to ...
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Scale normalisations in multinomial choice models

I am looking for advice on how to impose scale/location normalisations in the following multinomial choice model: The model $$ Y=argmax_{y\in \mathcal{Y}\equiv \{0,1,2\}}U_y(X)+\epsilon_y $$ or, ...
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Is the decision surface for a Probit model linear?

For example, if we threshold our classification on $0.5$, is the decision surface necessarily linear? It is linear for Multinomial Logit models, but it's not obvious to me that it is for Probit ...
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Interpretation of multinomial logistic regression

I ran a Multinominal logistic Regression with a set of categorical variables: Independent variables: characteristic1: Yes, No, Unknown. characteristic2: Yes, No, Unknown. Dependent variable: ...
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How to interpret GEE parameter estimate for Multinomial Ordinal Data

I have the following experimental design. There are four diet charts (A, B, and C, D). For each diet, a group of 25 subjects (1, 2, 3…25) was on each of those four diets. And they are supposed to ...
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ANOVA instead of multinomial logistic regression

Imagine experiment in which we show three cars: red, black and violet to responders and ask them which one is 'the coolest'. Question is: is their choice affected by their age? Now we have two ...
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Standard errors in R, package emmeans

I am fitting a multinomial logit model in R by using the multinom() function in the nnet package. I would like to retreive the proportions in each class for the two ...
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Probability of choosing the degenerate branch in a nested multinomial logit

This may be an obvious question, but I'm flummoxed. Let's say I've got a nested logit model with a degenerate nest—say, a healthcare choice model where the branches are Home vs. Hospital. The Home ...
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Why are the coefficients in a multinomial logistic regression a matrix?

I am conducting an analysis in which I have 3 different groups and a set of 80 continuous variables that I think can discriminate between the 3 groups. I want to: see if indeed I can discriminate the ...
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In multi-class logistic regression, does SGD one training example update all the weights?

In multi-class logistic regression, lets say we use softmax and cross entropy. Does SGD one training example update all the weights or only a portion of the weights which are associated to the label ? ...
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How can I evaluate the likelihood of a set of parameters in an mlogit model?

I estimate a conditional logit model using the mlogit function in R's mlogit package. This returns parameter estimates, likelihood, etc. I'd like to supply a ...
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Definition of softmax function

This question follows up on stats.stackexchange.com/q/233658 The logistic regression model for classes {0, 1} is $$ \mathbb{P} (y = 1 \;|\; x) = \frac{\exp(w^T x)}{1 + \exp(w^T x)} \\ \mathbb{P} (y =...
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Confidence Interval for Multinomial Elastic Net Predicted Probabilities

I am building an application which involves multinomial logistic regression models with the elastic net penalty using the glmnet-library on automatically collected data in R. My interest in particular ...
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Bivariate/multivariate models for multinomial response variables

I need to fit two categorical (potentially correlated) response variables (each has three classes) on a set of explanatory variables, while considering for the response variables' correlation. What ...
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Binomial-logit-normal

I'm watching a pool match and at the start of the first game the person next to me says "I think that the chance of player A winning the first game is $.700$. If he wins that I think the chance of ...
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An idea for multinomial logit model

I am running a multinomial logistic regression. I have a sample size of 500. I regressed the four categories/segments (A, B, C, D) on several independent variables including the intercept, setting A ...
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Questions on Bayesian Softmax Regression [closed]

My question is about how to actually do this both rigorously and practically. Allow me to elaborate. Suppose that we have data $(x_1,y_1),...,(x_N,y_N) \in \mathbb{R}^p \times \{0,...,k-1 \}$. I'd ...
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Repeated measures mixed model multinomial logistic regression

I have 1 continuous IV (cognitive ability) and 1 ordinal IV (task difficulty), that predict a categorical DV with 3 levels (type1, type2, type3), hence the multinomial logistic regression. Each ...
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How to estimate a model using Maximum Likelihood with Missing Data in Independent Variables in R?

I would like to estimate a multinomial logit model (MNL) on a data set where my independent variables have missing data. I do not what to exclude the data with missing values or use multiple ...
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Number of Parameters in a Multinomial Logistic Model (Varying Sample Sizes Across Dependent Variable Groups)

I have a dependent variable which consists of an unordered set of 12 groups (1, 2, 3 ... 12). I'd like to fit a multinomial logistic model, with group 1 as the reference class (essentially a series of ...
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Comparing multinomial logistic coefficients across groups

I have a multinomial logistic regression model - 1 DV with 3 categories and 5 IVs (4 continuous and 1 categorical). I would like to test whether my effects differ between different ethnic groups. Is ...
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Intuition behind multinomial logistic regression

I need some clarification in my understanding of what's going on under the hood of multinomial logistic regression (MLR). I have a nominal (not ordinal!) dependent variable $Y$ that takes values $A$, ...
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limit on number of alternative specific variables in multinomial logit

I am trying to understand the multinomial logit model as presented in chapter 2 of "Discrete Choice Modelling and Air Travel Demand: Theory and Applications" by Garrows, and I've come across a line ...
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sample size calculations for adjusted odds ratios in multinomial logistic regression

I have the following study set. The variables are given by: $$\begin{align*} x_1 &= \begin{cases} 1 & \text{if patient has a particular parasite}\\ 0 & \text{if not}\end{cases}\\ x_2 &...
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Distribution of outcomes in multinomial logistic regression

I have a sample of households where no data on children was collected for certain years. I wish to impute a discrete number of children, an integer, to households based on a vector of characteristics ...
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114 views

Multiple logistic regression with a categorical response value and categorical predictors

I am trying to perform multiple logistic regression with a categorical response value and categorical predictors. I have about 500 samples. These samples have discrete MICs that fall into 10 ...
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136 views

How to interpret the coefficient of the reference group in multinomial logistic regression

Assume that we have k classes and m samples, and each sample contains n features, then the ...
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35 views

Multinomial Logit Regression

I have 3 response Variables 1,0,-1 based on an increase,no change and decrease in the counts. I want to use a model which will compare the decrease or increase with no change using a set of ...