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Questions tagged [ordered-logit]

The ordered logit model (also known as ordered/ordinal logistic regression) is an extension of the logistic regression from binary dependent variable to an ordinal dependent variable. A widespread special case is proportional odds model.

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interpretation of ordered logit regression with categorical independent variate

I would like to predict the quality of plants in certain area. I divided the quality of the plants in 5 groups; 0 to 5. And we've measured 5 different areas; control, 1, 2, 3, and 4. I ran a logit ...
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Best Suitable feature selection method for ordinal logistic regression

I have 33 variables my dataset, I need to omit some less significant features then, which is the "best suitable feature selection method " for the Ordinal Logistic Regression?
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ordered logit for non ordinal categories

I want to use STATA to analyse the determinants of fertility. My dependent variable is the number of children born from a woman. Is it possible to use an ordered logit or probit when the variables of ...
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odinal regression

I get an output of ordinal regression model using r. it has 3 levels but I can't understand how to interpret can you explain to me what is the meaning of 0/1 and 0/2? here logic is the predicted ...
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Missing one category while predicting with polr

I am trying to predict football outcome using an ordered logit model and I am using R. I used polr in R and everything works fine until the prediction part. the dependent variable is the result (home ...
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Ordered logit with different choice sets at different times

I have the following dataset: at time $t_1$, a person faces the following ordered choice set $y \in [0,1]$, and at time $t_2$, he faces the ordered choice set $y \in [0,1,2]$. Assume the utility is $...
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Ordinal Regression Interprataiton [duplicate]

I am trying to learn how to perform ordinal logistic regression, this time using SPSS (but it is not very important to my question). I used the following tutorial: Link to example And either I don'...
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Ordered logit and proportional odds assumption

According to Wikipedia, ordered logit regression relies on the proportional odds assumption. Suppose that the proportion of people in groups 1, 2, 3, 4, and 5 are given by p1, p2, p3, p4, and p5. ...
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Analyzing/modelling discrete numerical responses and determining associations based on categorical co-variates

I need and would be grateful for some advice regarding the analysis of some data that has been gathered and coded by a third party. The data is part of a project regarding performance in the health ...
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“Down” “Null” “Up” logistic regression

I am familiar with binomial (logistic) regression and with multinomial regression based thereon. Is there a technique specifically adapted to "trinomial" data, where the data can be represented -1, 0, ...
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Constraints across related dependent variables

I'm working on model that uses a set of features like track_type, driver_age and some lag variables to predict the number of <...
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Why do regression parameters change when adding more explanatory variables in ordinal logistic regression?

I have been using ordinal logistic regression with the ordinal package in R and the clm() function to complete an analysis of ordinal survey research data. In ...
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How is probability y = j|X calculated from an ordinal logistic regression model?

I have an ordinal logistic regression model fitted with lrm from the rms library in R, and am presenting results as prob y = j|X ...
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VGAM parallel=F model error (doesn't occur for parallel=T)

I was looking into the proportional odds assumption for a wine dataset from the archive. I used the code from the UCLA page to assess the assumption and completed the Brant test using the brant ...
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How Can I Test for Multicollinearity in my Categorical Predictor Variables when Doing Ordered Logistic Regression?

I have a dataset where my dependent variable measures 'How much Trump’s locker room video should have mattered in the election'. The categories are coded between 1-5, where 1 represents 'should not ...
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Ordinal logistic GEE sample size estimation

I am looking for ways of doing power analysis for ordinal logistic GEE (currently in SPSS, but open to attempting R or something else). My understanding is that this will not be possible in software ...
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132 views

Proportional odds assumption for multilevel data

I'm running model in which I analyze salary of recent graduates. People graduated from different majors and in different years. The dependent variable (salary) is measured using intervals, e.g., "less ...
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GBM with an ordered y variable

I would like to execute a gbm in python, preferable in the h2o framework. My y variable is an ordered one, from to 1 to 5. I see that h2o does not have an implementation of an ordered logit. I ...
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Mixed ANOVA vs Ordinal logistic mixed model?

I have two different groups, Treatment A vs Treatment B, with measurements for each individual in four different time points. That is a 2 x 4 design. The dependent variable is a discrete scale from 1 ...
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Intraclass Correlation Coefficient with Bayesian ordered-logit GLMM (STAN)

I am fitting a Generalized Linear Mixed Model for an ordered outcome, in form of an ordered logit, with random intercept and slope. For this task, I am going Bayesian by handling STAN through the ...
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Ordinal Logistic Regression: Predict Probability instead of Factor

I have a script in R that writes the model I want and predicts the factor based on a support scale. Basically 1-5 where 1 is the best and 5 is the worst. This script returns no errors and works well -...
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Predict results from a POLR model

is it possible to predict (in R with the predict function) probabilities from POLR (proportional odds models) without specifying all values for predictors. I might be dead wrong about this, but I ...
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102 views

How can I interpret Generalized Ordered Logit model output?

As the title may suggest, how can I interpret the coefficients from generalized ordered logit model output? I know a little bit about interpretation of logit model, not generalized ordered logit model ...
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Is dummy coding required when spacing is meaningful (number of days)?

I apologise if this has been asked before. If so, please point me the right way. However, I have had a look and cannot find an appropriate answer. I am attempting to fit cumulative logit models ...
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Give an example probability for a specific ordinal classification task

I have problems with this exam problem (see image below) for machine learning. For my answer i assumed that $\hat{y}^{}_{0}$ and $\hat{y}^{}_{1}$ are the predicted classes. That means that $\hat{y}^{...
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Interpreting results of ordinal logistic regression - ordinal dependent variable with 5 levels and continuous predictor variable

I conducted my analysis in SPSS as follows: I fitted a generalized linear mixed model based on multinomial distribution with a logit link function. I did that using repeated measures longitudinal ...
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Predicted probabilities in a proportional odds model with categorical predictor

I estimate a proportional odds model in R with the polr model. The regression is basically the categorical educational achievements of parents on the categorical educational achievements of children: ...
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model checking in bayespolr

I'm trying to run an ordered logistic regression with the bayespolr function from the arm package. My response variable is categorical with three outcomes. I've got a few questions about this ...
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ordered logistic regression marginal probabilities hit ceiling

I'm running an ordered logistic regression with 3 classes, and I am able to predict the probability of each observation belonging to each class. For some reason one class' probabilities (top40) never ...
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How to model highly left skewed Ordinal Data

I have a data set of 16000 records of 5 ordinal variables(Customer Satisfaction(response variable), service, quality, knowledge, responsiveness) which are survey responses in 0-10 scale. All the ...
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143 views

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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Group variable in rank-ordered logistic regression

I used rank-ordered logistic regression in State for running analysis. I have 180 competitions. in each competition there are different teams competed with each other and they have ranks. Therefore, ...
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3 outcomes: one ordinal regression or two logistic regressions?

Imagine, for example, I am fitting a model with the following data: ...
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77 views

Fitting a ordered logistic regression model after a latent class analysis

I have a set of cross-sectional measures for a group of individuals and I would like to profile these individuals fitting a Latent Class Analysis. However, I also have longitudinal data at different ...
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How can I test the effect of a continuous IV (as well as other IVs) on an ordinal DV?

I have two instruments: a test, and a survey. Each participant has a test score, out of 240 (or a percentage out of 100%, it doesn't really matter.) The survey consists of 5-point Likert-scale ...
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Graphing predictions for ordered logit models [duplicate]

I have an ordered logit model and would like to create graphs such as the below, which states the predicted class for any given pair of x and y values. How can I do so, preferably in R? R code for ...
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269 views

How to plot the calibration curve for an ordinal logistic regression model applied to a test sample?

I'm doing a validation study of an ordinal logistic regression model that was made with the lrm function of the rms package in R. How can I plot the calibration curve for the model when applied to new ...
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Ordered Probit Model in R: Latent Variable and Threshold Parameters

I have recently started to improve my methodological skills and programming in R. For a study term paper I now want to run an ordered logit/probit model. The data I use are taken from the European ...
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Connection between logit model and power law distribution

I am wondering whether it is appropriate to make a connection between the use of a logit model and a power law distribution. My dependent variable is categorical and ordinal, therefore I am fitting a ...
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107 views

Ordinal response and ordinal predictors

I have recently applied a questionnaire to our students to understand their likelihood to use SCRUM for future projects in their curricula. Most of the predictors and the response variable are 5-point ...
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202 views

Retrieving p values in R, using clm()

I have run ordinal regression in RStudio using two different packages, relaxing the proportional odds assumption for predictor PROXIMITY. My ordinal response has 3 ...
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What is an intuitive but accurate way to explain the results of an ordinal regression?

Consider an ordered logistic (i.e., ordinal) regression, where a binary predictor variable increases a response variable that measured on a 4-point scale: ...
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543 views

Help with the rank-ordered logit model (exploded logit model)

I am hoping for some help with rank-ordered logit models. I get logit models, but Im having trouble when there are multiple levels, and when these are ordered. Moreover, I'm uncertain how to interpret ...
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Update: Include house ownership and house cost in a model

I would like to include house ownership (binary, 0 no, 1 yes) and property cost (continuous, logged) in an ordinal logistic model. If a respondent does not own the house where he/she lives, the value ...
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How do I know if my Ordered Logistic Regression is a good model?

I have a few questions about Ordered Logistic Regression Model (OLR). In general, how do I know if this is my model is good, and how do I enhance it? Using this example from https://stats.idre.ucla....
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1answer
581 views

Simulating data for an ordered logit model

I am currently working on an project where my dependent variable is available in the form of a Likert scale from 1-5. But before I will run my model on real data I want to test it on artificial data, ...
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187 views

Two-part model ordinal data

A response scale has the categories (strongly agree, midly agree, midly disagree, strongly disagree, do not know). A two-part model uses a logistic regression model for the probability of a DK (don't ...
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1answer
60 views

How to include variables which are highly correlated in ordinal logistic model?

I am building a driver model to understand what makes my survey respondent a Promoter/Passive/Detractor. We have used survey satisfaction drivers as my independent variables.Now Fast and Friendly ...
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What regression models can choose between more than two categories?

Logistic regression creates a model that predicts one of two possible responses for a given set of predictors. What if I want to choose between three responses? I tried this by using a logistic ...