A multivariate, discrete probability distribution used to describe the results of a random experiment where each of $n$ outcomes are placed into one of $k$ nominal categories.

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How to calculate marginal effects for categorical covariates using mlogit in R

I am trying to use the mlogit package in R and have been following the vignette trying to figure out how to get the marginal effects for my data. The example ...
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13 views

Selection bias correction and a multinomial logit

I have a data set for a number of people making 2 decisions - where to live; and how many hours to work. For every observation with a non-zero amount of work, there is an observed wage. I've assigned ...
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19 views

Clarification on interpreting Wald's test and Likelihood ratio tests

I am running multinomial logistic regression analysis on my data. The response variable is the number of calves produced each year (0,1, or 2). I am trying to evaluate the influence of the X ...
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1answer
41 views

Binary or Multinomial Logistic Regression in SPSS: Interpretation and Reference Categories

I am trying to analyze my data using Multinomial Logistic Regression whereby my dependent variable is a clinical outcome (sick vs healthy) and 1 independent variables (Factors) are in several ...
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31 views

multinomial logistic regression with alternative specific variables

I am working on a multinomial logistic regression problem which involves features from the dependent variable. It might be better to describe the problem by using the example in mlogit mlogit manual ...
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1answer
23 views

Multinomial logistic regression low classification rate

I am running a multinomial logistic regression with SPSS and I have encountered a problem (?) with my data. I have a dependent variable (DV) with three categories, five independent variables (IV) as ...
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1answer
33 views

multiple choice data simple logistic regression or multinomial logistic regression

I have a survey question where the respondent can check one choice or two choice maximum. Question looks like this: What is the more important characteristic when you buy chocolate? ...
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1answer
49 views

Logistic / multinomial regression as two / multiple Poisson regressions?

Can we instead of doing logistic or multinomial regression do two or multiple Poisson regressions and then combine Poisson predictions to get probabilistic predictions? If yes, how should we transform ...
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26 views

Updating a Dirichlet distribution with partial data

I've got some categorical data where each observation has multiple attributes, and I want to make a probabilistic model of this using Dirichlet distributions. For example, in the two dimensional case ...
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1answer
16 views

Calculate that at least n number of x values occur from multinomial distribution

Let's say X can take on 5 values X<-1:5 each of the 5 values occur with some probability: ...
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22 views

Better prediction models with polling data?

I've been working on a project on measuring polls' accuracy in complex contexts (more than two candidates) where there are a small number of inaccurate polling data points. I thought it would be the ...
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1answer
32 views

Difference between normal distribution and multinomial distribution

I would like to ask the difference between the normal distribution and the multinomial distribution because I don't know when to use each of them. I know the normal distribution is used for continuous ...
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1answer
22 views

Issue with controlling confound in multinomial regression analysis; different results when removing kids on meds

I examined the influence of ADHD on abnormal bodyweight in a very large, national sample of children. In my multinomial regressions, I controlled for several specific confounds, which have been shown ...
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Is there an extension of multinomial process models that can model several dependent variables?

In the setting of psychological experiments, where a categorical response has to be given, the same response can, in theory, be generated by different latent processes. For example, in an experiment ...
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1answer
18 views

Multinomial chi square with small expected values

I'm studying extinction in Austronesian languages, and am trying to find out if a subset of 384 languages is randomly selected with respect to extinction risk from a population of 1249 languages. ...
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27 views

Explaining MCMC sampling for a Multinomial Distribution and missing at random

I understand how MCMC works, and I understand how Multinomial Distribution works. I have a dataset some of the data are missing at random (MAR). I cannot connect these two dots together (MCMC -> ...
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1answer
33 views

Comparing regression coefficients across groups in multinomial logistic regression

Suppose that I fit a Bayesian multinomial logistic regression model where the dependent categorial variable indexes $x$ groups, and the predictors are the same across groups. I now have $x - 1$ sets ...
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45 views

Model selection of multinomial logistic regression for 2x3 contingency table

I want to analyze a 2x3 contingency table using multinomial logistic regression and I hope to be able to do it in Matlab or in R. I have looked around in old threads, but haven't been able to find a ...
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13 views

Compute confidence intervals for multinomial proportion

I need to compute the confidence intervals (CI) for a multinomial proposition. I am not a statistician but I can understand basic stuff... Looking around I have found this resource that explain how ...
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25 views

Random multinomial sample, with some restrictions

Given a list of $k$ non-negative integers $m_i$, $i=1,...,k$, and a positive integer $n$, with $n\ge m +k$, where $m=\sum m_i$. I need to generate $k$ random positive integers $n_i$, such that $\sum ...
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41 views

Analyzing discrete choice panel data with mlogit in R

I searched around and saw some high level discussion on mlogit and discrete choice panel models (here and here) but I need a more concrete answer than those. I am hoping somebody can point out what I ...
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37 views

How to Obtain “Right” Parameters of Multinomial Logit Model (or Other Conditional Models) in R?

I started to use the function multinom of R package nnet in order to fit several conditional ...
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1answer
58 views

Multiclass logistic regression update algorithm

My question pertains to section 2, called "Multi-class Logistic regression", of this pdf, especially the update rules. (The entire section is only a couple of paragraphs.) Everything seems to make ...
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1answer
42 views

MCA vs Multinomial Logistic Regression

Lets say I have made survey using a sample of a given number of people, containing a set of 25 questions that have 6 possible answers (Fully agree/ Partially Agree/ Neutral/ Partially Disagree/ Fully ...
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15 views

mlogit query with multiple options: response rate not good for third variable

I am stuck with one query on mlogit. I have three options (0,1,2) for prediction of probabilities. The model equation is: ...
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19 views

Additive Index: Count data or multinomial?

I would like to use an additive index, validated by Mokken analysis, as a dependent variable in a logistic regression model for categorical dependent variables. The index consists of adding values ...
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39 views

How to estimate an mlogit (R package) model with a fixed (offset) variable

I am trying to estimate a multinomial logit model using an offset variable with the mlogit package of R Using the syntax here [https://stat.ethz.ch/R-manual/R-devel/library/stats/html/formula.html] ...
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79 views

How to compare frequency distributions between 3 groups

I have characterized cells into 6 categories and want to compare the percent distribution of the different categories at 3 time points. Once I figure that out, I actually have additional treatment ...
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36 views

Can Dirichlet and multinomial distributions be defined from their univariate distributions this way?

For Dirichlet distribution: $X := [x_1, \cdots, x_K] \in [0,1]^K$, $x_i \sim {\rm beta}(\alpha_i, \beta_i)$ and $\sum x_i = 1$. Can we say the distribution of $X$ is a Dirichlet distribution? If ...
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83 views

I have a problem with bayes and train lines

I have this problem which I can't fully understand it: Assume you have entered in a foreign city of unknown size. At entrance you see a tramcar with number $100$. Let us assume that the tramcar ...
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1answer
46 views

Ambiguity with multinomial logit models

I have always thought that, when dealing with multinomial logistic regression, the idea was to linearly model the "logistic" functions of the probability densities of the different response categories ...
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35 views

Margin of error for non-dichotomous data

I am trying to calculate the margin of error for specific survey questions. I know how to calculate this if the data are dichotomous (i.e., a 75-25 or 60-40 split). But how do you deal with questions ...
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1answer
20 views

How to test if a value is over-represented in one sample vs another

I have two multinomial data samples that both have N discrete categories. I know that a Kolmogorov-Smirnov test will let me know if the distributions of the two ...
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1answer
50 views

Integration problem in Bayes factor calculation for multinomial model

This is one integration problem I encountered during the calculation of Bayes factor between two models given data $D$ One of the model, $M_0$ assumes the data accords to multinomial distribution, ...
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1answer
31 views

Predictor variables in Multinomial Logistic Regression

Is it always better to have categorical predictor variables when performing a multinomial logistic regression analysis? or can it be done using continuous predictor variables? If a predictor variable ...
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24 views

Does the more complex model necessarily have a lower deviance?

I am aiming to compare the deviances of two models, an ordered probit and a multinomial probit, using the likelihood ratio test (obviously using the same data). However, I systematically obtain a ...
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32 views

How can I sample from a multinomial distribution with a fixed expected number of remaining categories?

I have a population of entities associated with different categories, say blue 50000 red 300 green 80 yellow 10 pink 6 orange 3 white 2 The ...
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1answer
409 views

Categorize continuous data effectively (taking into account a response variable)

I wonder what are the better approaches to categorize continuous data (e.g. age) than dividing them with the use of quantiles and cut function (in ...
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8 views

statistical test for 3-preference choice design

We collected data from 40 animals in which we recorded the total time the animal spent in each of the 3 possible chambers. Thus, for each animal, we have three times (one for each chamber) and those ...
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1answer
114 views

Problem with building mlogit model (with no alternative specific variables)

I am confused with using mlogit package to build a multinomial logit model. In my data the only variables I have are the individual specific variables, to be ...
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2answers
190 views

Why does nobody use the Bayesian multinomial Naive Bayes classifier?

So in (unsupervised) text modeling, Latent Dirichlet Allocation (LDA) is a Bayesian version of Probabilistic Latent Semantic Analysis (PLSA). Essentially, LDA = PLSA + Dirichlet prior over its ...
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27 views

Multinomial goodness of fit

Suppose I generate a multinomial distribution with probabilities $p_i$, i from 1 to k. Now suppose I test it back using goodness of fit (chi square) with the probabilities we know. I read that this ...
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1answer
148 views

How to interpret the output of choicemodelr (rhierMnlRwMixture) in R

Can someone help me with this one? My Problem I just started using the R library choicemodelr and succeded in getting some beta values as a solution. But I wonder ...
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36 views

Show LRT statistic is non-negative for multinomial hypothesis test

This is a homework problem from Categorical Data Analysis by Alan Agresti (1.33) For testing $H_0:\pi_j=\pi_{j0}$, $j=1,\ldots,c$, using sample multinomial proportions $\{\hat{\pi}_j\}$, the ...
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3answers
522 views

How to validate a Multinomial Logit and Probit Model fit?

I would like to know how do you determine the performance of your models. That is, if you fit a multinomial logit or probit model for un-ordered discrete choice. What do you use to evaluate whether ...
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1answer
159 views

Oversampling correction for multinomial logistic regression

When modeling rare events with logistic regression, oversampling is a common method to reduce computation complexity (i.e., keep all the rare positive cases but just a subsample of negative cases). ...
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1answer
72 views

Multiple Bernoulli and Multinomial Distirbution

It's well known that language can be modeled by Multinomial distribution and Multiple Bernoulli distribution. So far I don't see any advantage of Multiple Bernoulli distribution representation over ...
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59 views

How to measure the accuracy of multinomial target?

I have trained a model that predicts a multinomial output. Would anyone know how the accuracy can be measured. The target takes on the following values: "Yellow","Red,"Green","Blue". I know that ...
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38 views

How to calculate the probability that the arithmetic mean of a multinomial process exceeds some value

I've been mulling over a problem that has something like the following form. I don't have a math or stats background so advice and answers at various levels, from terminological to strategic, would be ...
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1answer
36 views

how to derive the distribution of variable x conditional on x+y

The question is from a typical example for E-M algorithm. Let's say $(y_1,y_2,y_3)$ $\sim$ $\text{multinomial}(n;p_1,p_2,p_3)$, where $p_1+p_2+p_3=1$. How can we derive the conditional ...