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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When to use factor and ordinal factor?
When modeling a regression (glm.nb) one of my predictors is the number of sides of a road that has forest next to the road. This means my predictor can take one of three values. 0 = no forest on ...
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specific correlation for catagorical variables [closed]
I just wonder, can I determine the correlation for a data consisting of categorical variables. For example in school A, 300 out of 350 female students pass exam. While in School B, 100 out of 400 ...
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Which model for highly skewed data
The response variable in the dataset is highly skewed with a "ceiling effect". The errors of a fitted regression model, will thus also be skewed. I tried to fit a regression but as expected ...
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Group selection for Wilcoxon Rank-Sum Test
Are there any issues with only including a subset of the population in the paired samples? For instance let's say that we are comparing pain scores (ordinal values 0,1,2,3,4,5) before and after ...
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Linear Mixed Models for randomized clinical trial
I am working on analyzing data from a randomized clinical trial which is studying the effect of a mesh type on patient-reported pain. The 2 study arms are the 2 different meshes (biologic and ...
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Mann-Whitney U Test - Interpretation
I have conducted a survey and would like to assess whether men compared to women differ in their attitudes. At a glance, the means differ quite much, which is why I wanted to prove it statistically.
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How do I check proportional odds assumption for cumulative link mixed models?
I am using ordinal R-package to fit a cumulative link mixed model to an ordered, categorical outcome (5 levels) using logit function as the link function. The model is a random intercepts only model. ...
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Use of area under the curve to compare treatments with count ordinal data over time
I am working on questionnaire data, looking into bimonthly responses where "improvement" and "worsening" for different health parameters is recorded as counts or frequencies for a ...
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Computing the Mean of Twice-Measured Ordinal Variables for Individual Participants: Is it Valid?
I am conducting a 2x2 study with ordinal independent variables. Participants are asked to rate two different instances of the same independent variable condition. For instance, participants in the '...
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Hessian is numerically singular with a categorical predictor but not with a continuous one
Let's say I have a mouse performed a task for several runs, and for each run I assigned a score (ordered). I'm interested in the effects of medication (A, B) across runs.
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How do you use ordinal response data with several random effects to do robust hypothesis testing?
I want to explore the roles of lung presence and habitat on tadpoles' ability to tolerate low oxygen levels. My experimental design generated several measurements of "responsiveness" (on an ...
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What test should be used for one ordinal predictor and two continuous responses?
I have a longitudinal data set divided into 9 samples. The same individuals are measured repeatedly, but not all are present in all 9 samples (mortality). I want to predict two continuous variables ...
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Lavaan growth model: to treat endogenous variable as ordinal or continuous
I am modelling the trajectories of scores on two cognitive tests (i.e., PAL and SOS) measured at four time points. To do this I am creating separate latent growth curve models for each cognitive test, ...
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If a variable is coded as yes/no/unknown, is it categorical or ordinal?
The dataset has ten variables, and I am trying to conduct a cluster analysis. The ten variables are coded yes, no, or unknown. And I converted the character values ('yes', 'no', 'unknown') to numeric ...
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Which is the best correlation test for variables on the Likert scale?
Which is the best test for testing correlation between a 5 Likert scale (50 questions neuroticism scale) and one 4 Likert scale (16 question burnout scale) ?
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Dummy variables Zero inflated Ordered probit mods
I am relatively new to zero-inflated ordered probit models, and I've observed a pattern in the analysis of discrete data. In the research papers I've come across, many discrete variables are grouped ...
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Ordinal regression using statsmodels OrderedModel - basic interpretation
I want to run an ordinal regression in Python. My dependent variable describes a medical condition in an ordered manner (e.g. 0 = healthy, 1 = affected, 2 = very affected, 3= severely affected). I was ...
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Manually calculating partial dependence plots rpartscore tree
I am trying to generate partial dependence plots for my rpartscore model but I am not succeeding so far.
I have previously tried to use the package dpd but cant make it run with the probability ...
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Questions about Wilcoxon signed rank test
I wanted to conduct a Wilxocon signed rank test but stumbeld upon two questions that I am unable to solve on my own. I tested 2 types of interfaces for a software with the same ten people. I want to ...
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Mediation analysis with an ordinal mediator
I have to do mediation analysis for my research and my IV and DV are both continuous and mediator variable is ordinal (time spent on Instagram where categories are:
less that 30 minutes a day
30 mins ...
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Comparing 2 Likert Scales for 1 Population
I have two 5-point Likert scales (Strongly Disagree to Strongly Agree) and I want to compare the results within one population sample. I expect participants to choose 'agree' or 'strongly agree' on ...
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Logistic regression with binary and ordinal variables (SAS)
I have survey results (n=14, small size, I know) which scored several health measures from Poor (1), Fair (2), Good (3), Very Good (4), and Excellent(5). I want to see if having a physician (0=no, 1=...
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Can Ordinal data have a difference in mean if one is comparing the same group at different points in time?
I'm currently looking at a study where Ordinal scales are used to compare the effects of drugs on Alzheimer at different time points throughout treatment https://www.ncbi.nlm.nih.gov/pmc/articles/...
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How to organize an overlapping ordinal variables?
I am analyzing some data with attributes about how long it takes to commute, and it is an overlapping ordinal variable like the following:
Time
Number of People
1-5 minutes
10
6-10 minutes
24
less ...
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Comparing two identical surveys from 2019 and 2023. Each question has multiple items including "don't know"
I have this dataset made up of several questions, each with ordinal answers (likert-like) which unfortunately include a "don't know" option. The dataset is split in two: one portion from ...
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Difficulties to decide on model formulation and to identify dependent and independent variables
Imagine a disease whose exact mechanisms are unknown and can lead to different phenotypes. Although there likely is a continuum between the different phenotypes, these are categorized (as ordinal ...
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How to account for 'Don't Knows' / 'Not applicable' and missing data in survey data analysis and predictions?
First of all, I understand that this topic has been repeatedly covered in Cross Validated, and I have read through the forum but was unable to find a full answer to what I am looking for.
Context
I ...
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Most appropriate model for 0-10 scale integer data
I want to estimate the effect of a grouping variable (5 groups) on an outcome variable that is an integer and a scale from 0-10. So, for the outcome only scores of 0,1,2,... etc. are possible. This ...
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Can I use a categorical Variable as a numeric Variable? [duplicate]
I am currently working on a project involving a variable that represents the severity of a disease on an ordinal scale of 1 to 4, where 1 represents the least severe and 4 represents the most severe. ...
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Regression using proportions of Likert-type responses to questions as predictors for a continuous variable
Suppose I have data from customer surveys. It is Likert-like, but individual responses are not available. Results are given as proportions of total responses to each question. The count of responses ...
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How to analyze experiment with ordinal DV measured pre-post exposure?
I have an experiment with 3 conditions.
The dependent variable is ordinal (Likert style item on a 1-7 scale), and it was measured at 2 time points (before and after an event that all subjects across ...
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In R, how can I run a Spearman rank correlation using survey data?
I know that using the survey package to account for complex survey data, I can use the svycor() function from the jtools library ...
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Average Treatment Effect extensions for non-binary treatments
Average Treatment Effect (ATE) is a common measure to determine if a treatment (e.g. taking a particular medicine, you either take it or not) exert an effect on a particular target variable (e.g. ...
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Would it be appropriate to inspect the mean inter-item correlation for an ordinal scale?
I'm analyzing the data from a questionnaire using ordinal scales with five response options (Strongly Agree to Strongly Disagree).
I'm conducting my analysis using R, and have recoded the item ...
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Best statistical test for biological experiment with ordinal independent variable and binary outcomes over a time course
I am analysing a dataset with the following characteristics:
We have three different groups. The difference between them lies in different levels of expression of a specific gene (no expression, ...
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How should I analyse my ordinal data when there is a between-groups design?
I have asked listeners to rate some voices on 10 different questions. There were 2 groups of listeners. Group 1 had Set A of questions whereas Group 2 had Set B. Listeners responded on a Likert scale ...
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Properly organizing Kruskal-Wallis for two different analyses
I have the following data:
Seven substances (hereafter S1–S7);
Inside each substance, I have 30 scores (10 for each of three layers (let's call them A, B, and C)). The scores (1–5) are also ordinal. ...
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Analyzing the impact of a binary variable on ordinal response by various levels of a continuous variable using the mgcv package for gam model
There is a dataset consisting of 1100 in vitro fertilization cycles from 800 patients, indicating that some patients have undergone more than two cycles. The dataset contains 1100 rows. Each cycle ...
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Categorical variable in mixed effects?
I have a study like this: We recruits 20 teacher to participate in the research study. We use a step-wedge design where 10 of them are randomly assigned to a group that will receive an app and 10 ...
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Categorical ordinal and dummies
I have a feature categorical ordinal variable (i.e. consumer credit score), that I use to predict a target (i.e., apply for a mortage or not)
I have two options: process it as categorical, or encode ...
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If my sample size is large, is it ok to conduct a linear regression with a 7-point Likert item as a dependent variable?
Imagine that I have one variable from a 7-point Likert item, and my predictor is a categorical variable with three levels. Imagine that my sample size is 100. Can I run a linear regression lm(...
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Least squares method for ordinal variables
Does the least squares method for regression assume that the regressors and response are continuous? In particular, I would like to fit a regression line for ranks. Can I use the least squares method ...
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is a threshold model on ordinal data ~ a link function? SEM OpenMx
Are anyone familiar with OpenMx's capacity for handling ordinal data in SEM using a link function like ordered logit or probit (Stata gsem does this)?
Some folks have highlighted issues with feeding ...
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What are considered "voodoo fit indices" and "true"/"fake" standard errors? SEM CFA
In a conversation about fitting CFA with clusters and sampling weights (inverse probability weights) for ordered/ordinal/categorical data in R Lavaan, fit indices (GoF) were referred to as "...
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MIxed Model Ordinal Regression Drops Random Intercepts
Please could you help me?
I have been trying for quite some time to fit a mixed model with multiple binary and continuous predictors and an ordinal dependent variable. Subject ID defines the random ...
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Correlations can be compared with the Comparing Correlations ('cocor') package or R - but what if one of the variables is ordinal?
Let's say I want to compare the correlation of BMI and blood pressure in two independent groups and see, whether there is a difference between the correlations (whether the correlation is stronger in ...
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Is fixed-effects ordered logit models (feologit in Stata) suitable for matched case-control data?
Does anyone happen to be familiar with this method: fixed-effects ordered logit models (feologit in Stata)? In this paper: https://journals.sagepub.com/doi/pdf/10.1177/1536867X20930984
In the paper, ...
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Bayesian analysis - logarithmically increasing predictor, categorical outcome
I'm new to Bayesian analysis. My predictor is a logarithmically increasing variable (10, 100, 1000..) and the outcome is a categorical variable which indicates correct/incorrect. I need to analyze ...
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Why are emmip( "response") y axis numbers not probabilities for ordinal regression?
I used emmeans functions (with help from this site) to obtain pairwise comparisons for different levels of variables in a model with interactions.
Interpreting an ...
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Counts in ordered categories as response
Trying to figure out the most appropriate family for a data type I'm not used to.
For each measurement, I have a bunch of attempts, with the outcomes falling into bins: failure, small, medium or large....
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