Simpson's Paradox is an example of the Reversal Paradox, where an association appears in several different groups of data but disappears, or even reverses in sign, when these groups are combined.

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Looking to identify a book by a top statistician with a chapter on Simpson's Paradox

It was more than 20 years ago. I had just gotten acquainted with Simpson's paradox. I was browsing in a bookstore and saw a book by an eminent statistician -- eminent in the sense that I had come ...
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Example distribution to match an example?

I am doing exercises from "Causal Inference in Statistics: A Primer", by Pearl et al (2016). In chapter 1.2 there is a training challenge that goes like: In an attempt to estimate the effectiveness ...
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When should we use the segregated as opposed to the aggregated data?

In the book "Causal Inference In Statistics" by Pearl et al., there is the following problem (study question 1.2.2.) A baseball batter Tim has a better batting average than his teammate Frank. ...
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Recovering hidden confounder in Simpson's paradox trends

I just watched a video of an interested talk from PyData LA: "Using Simpson’s Paradox to Discover Interesting Patterns in..." - Nazanin Alipourfard, Peter Fennell (https://www.youtube.com/watch?v=...
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Disclaimer: This is not a duplicate of How to resolve Simpson's paradox. As given in this blog, the following is the data of people on the titanic: This is the same data when divided on basis of ...
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I am playing with a toy data where the Simpson's paradox exists for two variables NO2 and temperature: A scatter plot clearly shows that the correlation between NO2 and temperature was reversed when ...
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Does Simpson's Paradox cover all instances of reversal from a hidden variable?

The following is a question about the many visualizations offered as 'proof by picture' of the existence of Simpson's paradox, and possibly a question about terminology. Simpson's Paradox is a fairly ...
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Intuition needed when using weighted average to explain Simpson's paradox

In Freedman's Statistics (chapter 2), the author uses Berkeley's admission statistics (that 44% men and 35% women were admitted to graduate programs in general) to illustrate Simpson's paradox: the ...
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Language data as as a ratio of the number of words?

I am analyzing language data (nouns, verbs, etc) of people with and without autism and all of them have different number of words. Option 1: Would it be best to count each result as a ratio of the ...
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Effect of combining predictor variables in a regression model

Let's say I first run a linear regression model Sales = f(TV Spend, Digital Spend). Now I add TV Spend and Digital Spend and run the second model. My second model is Sales = f(TV Spend+Digital Spend)...
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Any examples of generalisation of simpson's paradox to other metrics

Simpson's paradox is introduced on wikipedia using 'metrics' of success rates and regression coefficients, for the first (success rate of kidney stone treatments): How to resolve Simpson's paradox?...
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I probably don't have a clear understanding of the Simpson's paradox. Informally I know that the average of response Y1, grouped over all possible levels of factor A, can be higher than the average of ...
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Is Simpson's Paradox always an example of confounding?

Is Simpson's Paradox always an example of confounding? Or is it possible to have a Simpson's paradox effect without an extra variable lurking in the background?
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Is stagewised feature engineering/ selection an invalid approach? What to do when all the features are not ready at one time?

Suppose we want to build a regression or classification model. However, the features (independent variables used) are not all ready at one time. This is very realistic in business, because the data ...
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A way to show Simpson's paradox is happening in the data

I'm not entirely sure what I am talking about is Simpson's paradox, because an opposite relationship does not appear when you combine two data sets, but merely a different one. Still, I think it is ...
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Is this Simpson's Paradox on the Titanic data set?

With the well known "Survival of passengers on the Titanic" data set I get a strange behaviour by plotting the fare vs. the age (see below). Without a constraint on Pclass the correlation is positive. ...
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Simpson's effect is key to understanding potential pitfalls in medical research, particularly in the area of meta-analysis, where multiple studies with dissimilar methodologies are brought together to ...
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What to look for to spot potential cases of Simpson's paradox?

I understand the basics of Simpson's paradox, but I'm not yet confident that I'd always be able to "avoid" it, or to spot cases where others have failed to do so. To be more precise, I'm not sure I ...
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Does adjusting for superfluous variables bias OLS estimates?

The usual textbook treatment of adjusting for superfluous variables in OLS states that the estimator is still unbiased, but may have larger variance (see, for example, Greene, Econometric Analysis, ...
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Suppose you constructing model whose training data is cumulative in nature; meaning each year you can add new observations with all prior observations being kept the same. (e.g. training set is non-...
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Understanding Simpson's paradox: Andrew Gelman's example with regressing income on sex and height

Andrew Gelman in one of his recent blog posts says: I do not think counterfactuals or potential outcomes are necessary for Simpson’s paradox. I say this because one can set up Simpson’s ...
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Why signs of coefficients change when doing multivariate vs. univariate logit regression? [duplicate]

Excuse my dumb question, but I did an univariate logistic regression where the sign of the coefficient of my variable was negative (and it was significant). Once I have input it into a multivariate ...
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Simpson's paradox is a classic puzzle discussed in introductory statistics courses worldwide. However, my course was content to simply note that a problem existed and did not provide a solution. I ...
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Simpson's Paradox, Combining data across confounding variable when few values are missing

The statistical analysis of experimental data that I have to perform could be described as follows. Three drug treatments $D_1$, $D_2$ and $D_3$ were tested across three groups $G_1$, $G_2$ and $G_3$. ...
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Does Simpson's Paradox affect if the researcher can conclude that alcohol consumption is related to gender?

I am preparing for my statistics final and have this question in the review package to answer: I understand the hypothesis portion of the question. How should I approach the first question: Can the ...
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Which hospital should be chosen? One has a higher success rate, but the other has a higher overall success rate

I have a question about something that my statistics teacher said about the following problem. My question isn't even about the occurrence of Simpson's paradox in this situation. My question is simply ...
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Consider a scenario where a two-way contingency table is analyzed by a chi-squared test of independence and a significant result is found. Now, it turns out that this table is an aggregation of data ...