# Tag Info

### If a variable is coded as yes/no/unknown, is it categorical or ordinal?

This cannot be answered without knowing exactly what 'unknown' means in your dataset. If 'unknown' refers to missing data, then it's likely best to replace them with 'NA' and analyse the variables as ...
• 18.9k
Accepted

### Where is there is only set of odds ratio in ordinal logistic regression?

The reason that an ordered logit only gives you one set of odds ratios is that it assumes (maybe correctly, maybe incorrectly) that one set are all that you need. The model is governed by something ...
• 5,077
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### Why is Pearson's r suboptimal for a correlations involving an ordinal variable?

The problem with Pearson correlation on ordinal data is that it's derived from covariance, and covariance is a statement about the differences between the observed data and the mean of the data (or ...
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### How to choose between ordered logit and ordered probit regression?

It is not the outcome distribution that determines the best ordered choice model. What matters is the error term distribution in the underlying random utility or latent regression model (given the ...
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### Binary logistic regression results interpretation when one IV is ordinal

It doesn’t seem like you should be restricting answers to only SPSS users as this is a broad misunderstanding of statistics and interpreting a model and not anything specific about implementing SPSS ...
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### Is it possible to conduct a regression if all variables are ordinal?

Relying on SPSS is quite limiting. If both Y and the Xs are ordinal and the Xs contain more than 3 categories there is only one completely satisfactory solution in my opinion. Use a Bayesian ordinal ...
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### ordinal logistic regression with multicollinearity among the independent continuous variables

First, if $C = C1 + C2 + C3$ then you have perfect collinearity and the regression will "blow up". You need to eliminate at least one of these variables. This is true for any kind of ...
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### If a variable is coded as yes/no/unknown, is it categorical or ordinal?

Reading the very interesting discussion here, I'd like to make a rather philosophical point that may be controversial, but is in my view well illustrated by how the discussion goes. The point is this. ...
• 26.2k
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### interpretation of trends in ordinal regression with emmeans

It always helps to look at documentation. emmeans offers several mode settings for ordinal models. The default is on the latent scale. For examples, please see this ...
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### Lavaan growth model: to treat endogenous variable as ordinal or continuous

I'd treat this as continuous. Treating data as ordinal where there are a large number of categories can lead to computation / identification problems.
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### Which is the best correlation test for variables on the Likert scale?

That depends on whether you want to regard the Likert scale as ordinal or interval. Technically, it is only ordinal. We don't know that the differences between levels. So, then, you would use rank ...
• 125k

### Regression with categorical variables only?

Your variable with preferences regarding a certain restaurant (1--5) is clearly ordinal, so you should look into ordinal regression. There are many posts on this site, some: Ordinal regression vs. ...
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### Can logistic regression predictor variables be nominal?

First, the Charlson comorbidity index is not nominal, it is ordinal. Indeed, if you use the calculator from MdCalc that turns it into expectancy of living 10 more years, it could be thought of as ...
• 125k

One solution is to convert grades to GPA and then do a t-test or U test. A = 4, B = 3. C = 2. D = 1. F = 0 is the usual way to do this. Or, if you have covariates, you could use some form regression. ...
• 125k

### Categorizing responses on a likert-type scale for use in ordinal regression

Why do you want to make it ordinal? Ordinal independent variables are hard to deal with. (Ordinal logistic regression can be a good option when the dependent variable is ordinal). You apparently have ...
• 125k

### Ordinal independent variable (IV) and continuous dependent variable (DV)

You should use the DV that you want to analyze. There is no need for the DV and IV to be on the same scales, or have the same range, or anything else like that. Questions about how to use SPSS (or any ...
• 125k

### Multiple logistic regression with ordinal predictors

If your predictors have a natural order to them, then treating them as more continuous makes more sense, and can be interpreted much like any other predictor in a regression. The problem with treating ...
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### Where is there is only set of odds ratio in ordinal logistic regression?

This is explained in detail here (start with the first link to BBR). If you want to allow ratios of odds of $Y \geq y$ to vary with $y$ without restriction, use the polytomous (multinomial) logistic ...
• 95.9k

### Determine performance in which subject improves overall performance

You seem to have an ordinal response variable, but it is not clear to me (not knowing this grading system) what is the order, but you will know. So one modern way (probably less known when you wrote ...
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### Which statistical test should I use for ratings?

Your rating variable is ordinal, so do not use anova. Also, since each participant has rated 30 statements, you should not assume independence. Maybe try ordinal regression with ...
• 81.4k

### If a variable is coded as yes/no/unknown, is it categorical or ordinal?

Visualizations mkt's answer is correct in my opinion, but I thought I would briefly illustrate some of the choices that are possible. Let us suppose that $\text{yes} \geq \text{no}$, leaving what to ...
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### If a variable is coded as yes/no/unknown, is it categorical or ordinal?

An interesting take on this: If you encode "unknown" as some value between the level of "yes" and the level of "no" you are actually performing an imputation (a bad one, ...
• 63.8k

### How to choose between ordered logit and ordered probit regression?

It is futile to "plot the distribution of my data to see if it follows a logistic or normal distribution." As Dimitriy implied, the distinction between the logit and probit models lies in ...
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### $\chi^2$ is insignificant when Spearman's $\rho$ is significiant (and vice versa)

There should be no surprise, as this are testing very different hypothesis. I get the following contingency table from your data (reading the .csv version) ...
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### Repeated measures for ordinal categorical variable analysis in r

A comprehensive solution may be obtained by forming an ordinal semiparametric model such as the proportional odds (PO) model. The PO model is a full generalization of the Wilcoxon and Kruskal-Wallis ...
• 95.9k
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### Linear Mixed Models for randomized clinical trial

For answers to your questions: Should time be continuous or categorial? As some have already noted, your time variable does not have equal intervals, so it probably wouldn't make sense to use as a ...
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### Mann-Whitney U Test - Interpretation

One thing you can do is ordinal logistic regression, where attitude is the dependent variable and sex is an independent variable. You will have to check the assumptions of the model, but this is a ...
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### Would ordinal logistic regression be appropriate in this case?

Assuming that your outcome is a discrete, ordinal measure, the textbook recommendation would be to use ordered logistic regression. However, you will find that scholars sometimes use OLS instead of ...
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