# Questions tagged [multinomial-logit]

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

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### Predictive analytics exam topics: Binomial and multinomial logit (conditional, ordered), conjoint analysis, limited dependent variables [closed]

What types of questions did you find challenging on an exam which covers these topics? I'm preparing for an exam which covers the topics above and looking for additional review questions to work out ...
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### What does scale heterogeneity mean in the generalized multinomial logit models?

I have learned that one property of multinomial logit models or the data used to build these models is scale heterogeneity. What does Scale Heterogeneity mean in the sphere of multinomial logit models?...
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### How scale heterogeneity can be a source of correlation?

First off, I'd like to put this clearly that I am new to logit models and I am trying to learn their basics. So far, I have understood that in the sphere of multinomial logit models and MXL, there are ...
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Suppose we have three alternatives $\{A,\;B,\;C\}$ where the elements do not have order. Then, we commonly use the following definition of the choice probability: $$Pr[y=A]=Pr[s_A>s_B,\;s_A>s_c]... 0 votes 0 answers 11 views ### Within Group Correlation of the Nested Logit Model Does the nested logit model impose homogeneous within group correlation? Consider a nested logit situation where there are J-many limbs (the first level) and each limb has K_j-many brances. Here, ... 1 vote 0 answers 23 views ### Categorical model divergences/high parameter density near zero in Stan I'm working on a hierarchical categorical/multinomial logit model in Stan. I thought I'd expand my question to stack exchange to see if anyone has any suggestions on the statistical model, since it's ... 0 votes 0 answers 13 views ### Multinomial models with different expected probabilities? As an example let’s say we were picking different colour balls out of a bag at random, and we wanted to see if certain colours are picked more than others. Our response would be "colour ball ... 1 vote 1 answer 13 views ### NNET Multinomial Regression - Error in looping through multiple independent variables and extracting coefficients/std.errors I have a scenario in which I'm using multinom (from NNET package) to perform multinomial regression over a set of 100+ genes (a given gene is an independent variable in each multinomial regression). I ... 0 votes 0 answers 137 views ### Regression for 3 levels dependent variable While reviewing a paper, I came across the following problem: the authors tested two groups, let's call them A and B, in two different experimental conditions, X and Y. The outcome variable had three ... 1 vote 1 answer 54 views ### How to handle independent variable in regression where no relationship exists between samples I would like to use a multinomial logistic regression to get win probabilities for each of the 5 horses that participate in any given race using each horses previous average speed. ... 0 votes 2 answers 53 views ### Is there a statistical software package for the generalized conditional/multinomial logit model? I have a discrete choice model of moving from one state to the other, so alternatives=states. I have case-specific variables such as income, race, and gender. In addition, I have moving distance ... 0 votes 0 answers 12 views ### How can I estimate the variance of the error terms in a conditional/multinomial logit model? Conditional/multinomial logit models(CML) can be esimated by the Maximum Likelihood Estimation(MLE). The likelihood would consists of choice probabilities: \begin{equation} P_{ij}=\frac{e^{V_{ij}}}... 1 vote 1 answer 13 views ### Household vehicle ownership allocation based on vehicle sales data I have a household travel survey data, which consisted of the number of vehicle owned for each of the household, household income, job, and household size. However, the data didn't show the brand, ... 2 votes 1 answer 93 views ### Interpreting Results of Logistic Regression when both x, y variables are nominal I've been trying to analyze the result from my experiment. But since I'm new to the field of statistics, I'm struggling in every step, including the interpretation of results. I have 4 groups of ... 0 votes 0 answers 32 views ### Interpretation of Multinominal Logistic Regression coefficients I am struggling to understand my Multinominal Logistic Regression. This is my first time ever tackling such a model. Note that I was following this recipe. I am trying to predict the redemption rate (... 0 votes 1 answer 53 views ### Categorical independent variables for logistic regression I'm currently struggling to find a appropriate method to analyze my experiment. Currently, I have 4 groups of subjects, and each subjects made a choice between 3 options(A or B or No choice). Below ... 0 votes 0 answers 24 views ### mlogit and MCMCglmm in R I would like to ask your advice on the statistical approach for my research. My research is to investigate the relation between formant frequencies of phonemes (three vowels, /a/, /i/, /o/) and ... 0 votes 0 answers 15 views ### Choice Based Conjoint 'no-choice' MNL model validation I have conducted a CBC with each choice task consisting of 2 concepts and a no-choice option. For training my MNL model, I added a column to the dataset that takes the value one (for both concepts) ... 0 votes 0 answers 47 views ### Is it possible to implement ANOVA analysis with categorical dependant variable? I have some survey data which tracks the employment status of individuals over time. I am doing an analysis on the effects of different independant variables on occupation, and one thing I wish to ... 0 votes 0 answers 34 views ### how do I handle the issue of dependent observations in multinomial logistic regression model I have recently conducted a study where I built a multinomial logistic regression model to investigate whether keystroke logging analytics (e.g., pause time in writing, general typing rate, revision ... 1 vote 1 answer 50 views ### Fitting a multinomial glm for a very large dataset I have compositional data where for two groups, where each is represented by two ages, there are 100 possible categories for which I observed counts: ... 0 votes 0 answers 14 views ### How to select data and report a multinomial logistic regression for microbiome recently I have been working with gut microbiome data, like abundance and its metabolic content (but for purposes of the question this may be indifferent). I'm inexpert in the field of multinomial ... 1 vote 1 answer 36 views ### Too many categorical predictors in multinomial logistic regression I am not familiar with multi-class prediction so I apologize in advance if this questions seem very basic. Here is my dataset: So within the dataset, I am trying to predict which fare product is ... 0 votes 0 answers 41 views ### Multinomial Logistic Regression as a latent variable model I was reading the wiki entry for multinomial logistic regression https://en.wikipedia.org/wiki/Multinomial_logistic_regression#As_a_latent-variable_model and it states that we can view the multinomial ... 1 vote 1 answer 120 views ### should I use n-1 dummies variables or all variables for a multinomial logistic regression? Recently I have been working with gut microbiome data, like abundance and its metabolic content (but for purposes of the question this may be indifferent). I'm inexpert in the field of multinomial ... 1 vote 0 answers 12 views ### Condition logit model: Weighted mean of ratios of coefficients of subgroups does NOT equal the ratios of coefficients of the whole sample, why? I am well aware that when one splits the sample into subgroups (e.g. sex, country, whatever), and then estimates any logistic regression model, the coefficients are not comparable between (otherwise ... 0 votes 0 answers 18 views ### Looking for a scientific paper that explains the OneVsRestClassifier from scikit-learn In my Logistic Regression Model I am using (among others) the OneVsRestClassifier, as the simplest tool to get probabilities for a multiclass problem. I understand how it works and I understand that ... 1 vote 1 answer 119 views ### Interaction between alternative-specific and individual-specific variables in a conditional logistic regression I am interested in the moderating effect of a voter's political knowledge on the effect of a voter's candidate evaluations on vote choice. I am trying to estimate conditional logit models to analyze ... 0 votes 0 answers 82 views ### How does one compute standard errors for coefficients in multinomial logistic regression? I am currently engaged in a project to try and compute standard errors for coefficients for multinomial logistic regression. I saw answers with code in this post here How to compute the standard ... 0 votes 0 answers 48 views ### Kernel Multinomial Logistic regression in R I have a dataset of graphs/networks, and associated labels in R. I have read literature on graph kernels (e.g. Borgwardt et al), and can implement these with the ... 1 vote 1 answer 49 views ### How can a 'linear models' be used to predict the level of a categorical variable from continuous numerical variables? I am a 1st year undergraduate psychology student currently doing some statistics exercises following a class. The statistics topics we have currently covered is still basic, including the various ... 0 votes 1 answer 32 views ### multinomial logistic regression with many IPVs How should we refer to a logistic model where the dependent variable has more than two categories and you have more than one independent variables? Could it multivariable multinomial logistic ... 3 votes 1 answer 93 views ### How to estimate population proportions for colored beads in a jar Suppose I have a jar of colored beads. The jar contains about 15000 of those beads and they come in 10 different colors. I want to know whether there is a a difference between the true population ... 0 votes 1 answer 62 views ### Testing independence and setting constraint matrices in a multinomial logit model in R I have a data set the looks like this (called rand_df as this is a random subset from the much larger dataframe): ... 1 vote 1 answer 157 views ### Multiple imputation and inverse probability weighting for multiple treatment? I am analyzing observational study data. My predictor variable is tg4 with 4 categories (0,1,2,3) and my response variable is dm ... 0 votes 0 answers 29 views ### Reopening the question about conducting a three-step Latent Class Analysis in R I would like to reopen the question, which was already asked in this post (1) and (2), but due to the peripheral conditions and questions of the questioners, probably did not get the proper attention. ... 1 vote 0 answers 96 views ### Using a spatial tensor spline in a nnet:multinom multinomial fit in R I know that in library(mgcv) one can use spatial tensor spline smooths in gam fits with a cyclical spline basis for longitude as ... 1 vote 1 answer 48 views ### Categorical mediator and total effect estimation Let's say you have a linear variable (X) that has a causal effect on a final linear variable (Y) via a mediator which in turn is a categorical variable (Z).$$ X \rightarrow Z \rightarrow Y $$... 0 votes 1 answer 37 views ### Eliminating redundancy in Multinomial Logistic model At page 348 - Chapter 10.6 in The Elements of Statistical Learning (12th printing -2007), the logistic model for K-class classification is expressed as: p_k(x)={exp(f_k(x))\over \sum_{l=1}^{K}exp(f_l(... 0 votes 0 answers 22 views ### Dealing with "none" responses in discrete choice models I have data which consists of respondents' answers to a question on political party identification, as well as other covariates for the respondents such as income, age, etc. Respondents are asked to ... 1 vote 1 answer 26 views ### Model for percent resource allocation between groups I have a panel data set indicating each entities percent resource allocation among a number of different options. I have been using a logistic regression model to predict the share of allocation for ... 0 votes 0 answers 43 views ### Analysing data with multinomial logistic regression I am trying to analyse a dataset with multinomial logistic regression. The data looks as follows: 1 categorical dependent variable with 4 levels (Same-day delivery, Next-day delivery, Evening delivery,... 1 vote 0 answers 38 views ### How to calculate propensity scores for multiple treatments with different predictors? I use propensity score matching with one control condition d\in\{0\} and multiple treatment conditions d\in\{A, B, AB\}, where AB denotes the combination of (relatively unrelated) treatments A ... 0 votes 1 answer 20 views ### Multivariate logit: evaluate contributions of predictors to estimated probabilities In a logistic regression with multiple regressors, is there a way to analyze the contribution of the predictors on the dependent variable? (e.g. how would one understand why did the probabilities ... 3 votes 1 answer 222 views ### Softmax overflow AND underflow I am trying to use the typical Multinomial model: y_{i} \sim Multinomial(N, \theta_{1}, ...,\theta_{p}) where each theta is defined as: \theta_{i}=\frac{e^{V_{i} }}{\sum_{j} e^{V_{j}}} I have an ... 0 votes 1 answer 80 views ### Indicator function with equal sign for probability integral In the beginning of the book Train (2009, p.4) on "Discrete choice methods with simulation" we read: Deﬁne an indicator function I[h(x,ε) = y] that takes the value of 1 when the ... 0 votes 0 answers 29 views ### Can we have an explicit representation of inverse of a softmax function? As we know, logit is the inverse of logistic function in case of binary classification. Similar to this, I am willing to derive results for multinomial classification, for that I need to get an ... 0 votes 0 answers 24 views ### What does \tilde{p}_{ik} mean in the dual form of Multinomial Logistic Regression? Minimization of objective of dual Multinomial-Logit Regression:$$ \begin{array}{ll} \min _{\mathbf{w}} & \frac{1}{2 \sigma^{2}} \sum_{k=1}^{K}\left\|\mathbf{w}_{k}(\boldsymbol{\alpha})\right\|^{2}...
Suppose that there are 10 treatments, each of them applied to groups of $n_i=10$ patients (i.e. 100 patients in total). Three types of outcomes are measured on each group, defining categories \$C_1, ...