Questions tagged [ordinal-data]

Data with categorical values that can be ordered by magnitude, but the exact distance (spacing) between categories is undefined or unknown.

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19 views

How to compare sensitivity analysis results?

I have performed global sensitivity (Morris one-step-at-a-time) for two conditions, with/without treatment. The results are two list of parameters with according scores, e.g. ...
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22 views

Which model should I use for ordinal data if one or some variables violate equal slopes

I have running the data for an experiment. There are 3 independent variables in my data namely "Rhyme", "Meter" and "Lexicality" all with 2 levels (0/1) respectively. Based on these parameters the ...
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Relationship between ordinal and (semi) ordinal variable

I have the following problem. I have conducted a survey about how people have consumed media in a certain way. The scale of responses was 1=never to 9=always. Also I have recorded exam scores for a ...
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28 views

Combining customized contrasts + nested ANOVA (?)

I would like to get some advice on running a customized contrast analysis. I have looked at a few vignettes and I think I get the basic idea, but I'm not sure how to adapt them for my purpose. To ...
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1answer
27 views

Including a quadratic effect for an ordinal variable in a regression analysis

It's common for many datasets to have ordinal versions of numerical variables, such as age groups (e.g. "Under 20", "20-30", "30-40", etc.) or time groups (e.g. "Less than 15 minutes", "15-30 minutes",...
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Quantile Plot in RMS::orm [migrated]

I'm not sure if this question is more pertinent to CrossValidated or StackOverflow. I'm happy to migrate it if necessary. I'm trying to reproduce the plots from Roger Koenker's quantile regression ...
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Likert scale question as a dependent variable

I have a questionnaire with many items. The researcher defined several items to be dependent variables of interest for analysis. Some of them are represented by a single likert scale question with a , ...
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24 views

how to deal with ordinal variables for machine learning?

I have a data set that contains an ordinal variable. The variable is in ranking. 1st, 2nd, 3rd, 4th ... 30th I was pre-processing the data set and thinking 'if 1st rank is the best rank (highest ...
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8 views

Is it acceptable to use multilabel classification data to predict a continuous score?

If a model is given a multilabel classification problem is it appropriate for it to then, as opposed to just predicting the given labels, use those labels to create a scoring scale of ordinal ...
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11 views

Can Spearman's correlation be used to assess relationship of nominal and categorical data sets?

I've got 3 sets of data from 3 tests. In a health care scenario there's a set of tests to assess a specific pathology. The 3rd test is very time consuming and costly so the 1st and 2nd test were ...
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40 views

How to model qualitative body condition scores? Ordinal logistic regression?

I am after some advice on how to model qualitative animal body condition scores? My overarching research question relates to comparing the body condition of animals across seasons, locations, age ...
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Constructing ordinal variable for matching

I know for all the firms in my data how the R&D budget is allocated to three distinct groups based on how applied the research is. For example for firm X I know: 10% of R&D budget is spend on ...
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relation between one variable nominal and other ordinal

What is the best way to know the relation between two variables like gender (MAN/WOMAN) and opinion (Very Bad, Bad, Neutral, Good, Very good). (Nominal with ordinal) I think that with a chiq-...
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16 views

Neural Networks and numeric variables

I want to predict condominium prices with a neural network. Some of my variables are numeric but are not assumed to relate to the price in form of a mathematical funktion (linear, square, ...). For ...
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1answer
28 views

R: How can I represent partially-ordered time series in R?

I believe that this is a statistics rather than a programming question, though I am tied to an R implementation and hope for a reply in kind. I have data that constitutes several time series. I ...
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11 views

Continuous Dependent variable, ordinal and continuous as Independent variables

I have a numeric dependent variable, and I'm trying to run a regression model in R using a score (ordinal) and another numeric variable as predictors. Which is the appropiate model (and R code) for ...
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Rank correlation with only incomplete pairwise comparisons?

I am studying the online ad ecosystem and would like to study the relationship between prices advertisers pay to show an ad and the preferences of users. In particular, I have a set of observations ...
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18 views

pingouin rm_corr for repeated measure ordinal data in python?

I have a similar situation to this question: Repeated measure correlation in Python Where I have repeated measures from participants since they fill out a questionnaire each day. I can use pingouin'...
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1answer
97 views

5-point likert scale into low, medium, high categories?

I am designing a study where the objective is to collect the % for low, medium and high to populate probability tables. For example, my objective is to know what is the probability in % to have a {low,...
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1answer
25 views

In ordinal classification, how can adjacent accuracy be expressed mathematically?

Say that we have an ordinal classification problem where we have an ordered set of classes $\mathbb{C} = \{ C_0, C_1, \ldots, C_{K-1} \}$. We have $N$ samples, where the true and predicted classes of ...
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26 views

Statistical test for preference data through average differences or is other method more suitable?

I need your help. I'm designing a questionary and there I want test which version the people prefere. Which of the following methods is better and which statistical test for significance in each ...
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12 views

ordered variables in GLM vs GAM

I'm trying to find the best model from a dataset which mainly has ordinal variables (in likert scale). So, I don't know since I had to put in GLM as.factor do I ...
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1answer
39 views

Make predictor/variable less important in Neural Network

I have a question regarding my Neural Network. So, my data contains multiple users who filled in Likert-scale surveys regarding their happiness level (ordinal data). I am testing multiple ways to ...
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48 views

How to interpret output of measurement invariance analysis

I try to test the measure invariance of a scale (with a 1-factor-structure) across two groups (N_1 = 645; N_2 = 127) and have problems with the application as well as the interpretation. I'm sure they'...
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21 views

margins() on polr() model

I'm trying to work with polr instead of clm because with my large data set and a complicated model it requires a very large amount of RAM (300gb)... Margins works, withouot yielding SE, z, p-values ...
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1answer
29 views

Does it make a differences to a prediction model if a factor is ordered or not?

I want to build a prediction model where one predictor variable is a score of roman numeral I, II, III, and IV. I am using R and I currently store this feature as factor. This, however, is not ...
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Ordinal predictors treated as continuous in multinomial logistic regresion

Can an ordinal predictor variable (independent, 4 levels - 0, 10, 20 and 30) be treated as a continuous variable in a multinomial logistic regression? Thank you for your help.
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How to confirm more people selected “Agree” than is possible by chance [closed]

In the table below, how do I prove statistically that more people are in the group: "Sum of Agree", than is possible by chance? I do not know which test to use here, (although I am using the Extended ...
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15 views

Dichotomizing skewed variable or run a ordinal logistic regression?

I have a variable of tumor sizes that is skewed, i.e. fewer people have larger than smaller tumors for example. There are 4 levels to this variable (say 0-1 cm, 1-2 cm etc.) I want to see if there is ...
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35 views

How to Keep Missing Values in Ordinal Logistic Regression

I’m using mord package in python to do ordinal logit regression (predict response to movie rating 1-5 stars). One of my predictor variables is also ordinal but ...
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17 views

How to describe a split-plot ordinal logistic regression

I am having difficulties reporting a split-plot ordinal logistic regression. I get the concept of ordinal logistic regression involving a categorical representation of a latent continuous variable, ...
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23 views

Interpreting interaction odds ratios in ordinal regression

I have run an ordinal regression in R using polr from the MASS package. I'm trying to interpret an interaction. Both predictors are categorical. Here is an example: Predicting success in the job ...
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1answer
73 views

Finding trends in ordinal time series data

I am looking at patient data with clinical scores for each that run from zero to 6 (integers, where zero is best and scoring 6 on symptoms is worst). There are follow up scores on each patient (at ...
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38 views

Differences between cumulative link models (ordinal) and multinom (nnet) for fitting multinomial data

I'm trying to understand cumulative link models and how they differ from multinom models in R. Here's a simple example of a multinom model and plot output using the nnet package: ...
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1answer
16 views

Regression with ranked and truncated dependent variable

I'm struggling to find a model that will best fit this data. The dependent variable is the ranking of a observation based on how many votes it received based of a list of choices (number of votes is ...
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14 views

Can binary data be used in ordinal regression models?

Basically I have some code which runs a lot of calculations originally on some ordinal response variable and some predictor variables, and it is based on the VGAM R package. As such, it seems like it ...
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12 views

Moderation in ordered regression

For my thesis, I have to do some regressions in STATA. I am not very good with STATA at the moment, so I would like to check if some things are correct with you. Help is greatly appreciated. My ...
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What is the best way to handle ordinal features having numeric values in python? [closed]

What is the best way to encode ordinal feature? Is it by transforming it using OneHotEncoder so values going from 1 to 7 lets say would become head of new field feature. Or by using StandardScaler() ...
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53 views

Performing and interpreting a logistic regression using ordered variables in R

I'm currently working on my first larger project with self-collected data and only few guidelines. My dataset contains 29 variables, all of which are categorical and most of which are ordered (with 2 ...
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1answer
126 views

Random forest ordinal data

I want to estimate a Random Forest in some statistical language (SAS). This can only be estimated by setting the target variable as nominal instead of ordinal. Isn't it possible to estimate a Random ...
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1answer
35 views

Does treating trial number as a continuous variable for linear models lose information?

If I create a linear model where Trial number is one of the predictors, am I losing any information by treating it as continuous (when in fact it is actually discrete + ordinal)? I believe the answer ...
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Paired experiment with trinomial response - Analysis help!

I'm looking to analyze data (in SAS) from a trial investigating the effect of a particular protective padding on preventing skin irritation at multiple body locations among spinal surgery patients. (...
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1answer
21 views

How to handle clustering analysis of data which has different numbers of levels

For example, if i have data which is along the lines of ...
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46 views

Encoding Ordinal categorical data using Python

I am trying to encode ordinal data. I found a post which suggests a way to do it. Where to find a guide to encoding categorical features? This seems to make sense. For nominal data, I would do the one-...
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132 views

Mapping categories of probability estimation onto a continuous distribution

I have a model for turning bookmaker odds into probabilities by removing the bookmaker's over-round. This generally works pretty well but I've run into an issue with certain kinds of markets, ...
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2answers
99 views

Understanding p values in ordinal logistic regression in R

I'm trying to wrap my head around ordinal logistic regression outputs in R. I've seen some similar posts before and read many tutorials, but I feel like some things are missing. What I'm looking for ...
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6answers
421 views

How can I visualize an ordinal variable predicting a continuous outcome?

What is the best way to visualize the relationship between an ordinal predictor and a continuous outcome? So far I have the below, but I feel like this is lacking... The way I modeled it is I ...
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1answer
110 views

Interpreting odds ratios in ordinal logistic regression

I am trying to predict exam performance (below, average, above) based on whether participants attended a revision class. I am analysing my data in R using a proportional odds logistic regression. I am ...
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1answer
24 views

Kendals tau-b correlation with lots of 0 variance columns

I am writing a paper that is meant to establish that certain algorithms rank candidate values accross multiple problems in a different way. To do this, I take Algorithm A and run it on the candidate ...
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Wich analysis should I use for 2 or 3 ordinal predictors and 2 nominal outcomes?

I´m actually a bit confused.These are my variables: -->predictor Variables: Ordinal Variable X (Low-high), Difficulty (low-middle-high) -->control Variable: Confidence (low-high) -->outcome Variables:...