Questions tagged [multinomial-logit]
Multinomial logistic regression models a categorical dependent variable that can take on >2 different levels.
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Logistic Regression?
Can you use logistic regression if you have more than two options for the dependent variable. Instead of just a yes/no option I could have more than 2 options. I have 20+ predictor variables.
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Multinomial logistic regression assumptions
What are the proper assumptions of Multinomial Logistic Regression? And what are the best tests to satisfy these assumptions using SPSS 18?
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Alternatives to the multinomial logit model
I am trying to estimate a model of occupational choice with three choices. Are there any alternatives to using the multinomial logistic regression when handling such unordered categorical outcomes?
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Difference between multinomial logit and multinomial probit
Similarly to the question Difference between logit and probit models I am wondering what is the difference between a multinomial logit and a multinomial probit. And when should I apply which of the ...
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Interpreting coefficients for multinomial regression with >2 classes? [duplicate]
In R, I am fitting a model using the multinom() function from the nnet package. There is ...
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how to calculate manually propensity score weights for multinomial treatments where one of them is baseline
I want to get intuition into the calculation of propensity scores (PS) and inverse probability of treatment weights (IPTW) for a multinomial treatment using multinomial regression. One of the ...
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Survival: treat censoring as a competing risk and use multinomial logit
Suppose I am modeling survival with the hazard rate specified using logistic regression, and the model is adequate for the data. Now add censoring, and the model formulation becomes a bit more ...
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Why ordinal target in classification problems need special attention?
I have been working on an ML problem in which I want to predict an interval of money say, a, b, c, d that might be lent to a customer given its credit files, those amounts are represented on ordered ...
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What is the difference between fitting multinomal logistic regression and fitting multiple logistic regressions?
In an analysis where the dependant variable Y has 4 levels (say A, B, C, and D) and there are several independent variables (including important interaction terms), ...
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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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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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Assumptions behind multinomial logistic regression [duplicate]
What are the proper assumptions behind multinomial logistic regression? And what are the best tests to satisfy these assumptions in any statistical software? What are other suitable models, if those ...
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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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IIA assumption: difference logit and probit
Considering the following question about the Independence of Irrelevant Alternatives assumption:
Alternatives to multinomial logistic regression
It seems as if IIA is only a problem when using a ...
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Random effects for a mixed multinomial logistic regression in R?
I have a dataset in which individuals, each belonging to a particular group, repeatedly chose between multiple discrete outcomes. Something akin to:
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How robust is multinomial logistic regression to having a multi-label problem shoehorned into it?
Consider a situation where there can be membership in group $A$, group $B$, both groups, or neither group. If we wanted to predict group membership probabilities from some covariate information, this ...
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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:
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P(Y=k|X_1=x_1,X_2=x_2)=\frac{\exp(\beta_{k0}+\beta_{k1}x_2+\...
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Is it currently possible to run a multinomial logistic regression with random subject and item effects, in R? [closed]
I have a set of data in which participants get one of two types of items. I want to calculate if their responses are more likely to belong to one of X categories when they get one type vs. the other.
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Logistic Regression for non-binary classification (multi-class) in R
I am trying to use glm(family = binomial(link = 'logit')) for a classification task with 14 classes. I know that logistic regression is used in R for binary ...
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Is multinomial logistic regression symmetric?
Simple linear regression is symmetric in the sense that, if I regress $Y$ on $X$ or $X$ on $Y$, I get the same $R^2$ and result from the overall $F$-test.
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What standard error should I use with correlated clusters in maximum likelihood estimation of multinomial logit
I have a dataset with 14 clusters. Each cluster is a time series of 80 periods with autocorrealtion, and I am doing maximum likelihood estimation of a structural multinomial logit model. I suspect ...
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How to analyze the evolution of a multilevel variable with an interaction?
I'm doing an analysis in a frequentist approach where the dependant variable X has 4 levels (say A, B, C, and D).
This variable was studied in 4 timeframes: 2 years ...
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Overparameterization with softmax with neural networks
I have encountered some applications of the softmax (multinomial logistic regression) in neural network applications where the sum-to-one constraint is ignored (e.g. see this link or this link). That ...
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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 ...
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Discrete choice model with different choice set for each sample
Data
I have observational data of $N$ rows (samples). In row $n$ individual $k_n \in \{1, \ldots, K\}$ from a population of $K \ll N$ individuals chooses one option $y^{k_n}_n$ from $J_n$ options, ...
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Is a win-lose model for three Presidential primary candidates appropriate? Multinomial Logit model?
I have a dataset where each record represents a collection of variables for each of the counties in New York. Five variables represent the number of tweets in that geographic area for each candidate ...
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Discrete choice models; estimating probability of new alternatives
Let's say the set of alternatives are $j=1,2,...J$, where $X_i$ is the vector of subject-specific attributes for subject $i$, and $Z_{ij}$ is the vector of alternative-specific attributes for ...
