Questions tagged [regression-to-the-mean]
The phenomenon that on repeated testing a high value tends to be lower, and a low value higher.
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In repeated measures, how to distinguish regression to the mean from a negative lagged effect?
I have repeated measures for a quantitative variable "cry" for N = 52 participants (how much you cry at a given time), there are 30 repeated measures. The values range from 0 (not at all) to ...
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Controlling for regression to the mean in nonparametric survey response data - pre-post design - difference between groups
I have 920 pre-post responses to 5-point Likert-scale questions evaluating the impact of an educational intervention. I wish to test whether outcomes (change = post - pre) differed across different ...
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How control for a pre-treatment outcome $Y_0$ if is a strong confounder while avoiding regression to the mean bias for treatment effect on $Y_1$?
I'm facing a dilemma in a pre/post cohort matching analysis for a healthcare intervention:
Matching on the pre-treatment outcome $Y_0$ (a continuous variable) will likely lead to regression to the ...
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How does the law of large numbers relate to regression to the mean?
Intuitively, these two important statistical principles appear to describe two facets of the same phenomenon, namely that in the long run, any extreme occurrences get counter-balanced, and things tend ...
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What's complicated about regression to the mean?
Note: I am a bit of a novice when it comes to statistics and data analysis.
Reading the chapter on regression to the mean in Kahneman's Thinking Fast and Slow, I came across the following passage:
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Matching on pre-treatment outcome $z$-score in diff-in-diff analysis to avoid regression toward the mean bias in $ATT$ estimates?
There have been many articles (e.g., Chabé-Ferret (2017), Daw & Hatfield (2018), Zeldow & Hatfield (2021)) discussing the perils of matching on pre-treatment outcomes (such as patient's ...
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How to adjust estimates to account for regression to the mean?
Let us consider an example where we have a number of runners and an estimate of speed in mph for each runner. The estimate for each runner may be based on an equal or unequal number of independent and ...
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Can I use the early response to a treatment to predict the full effect? - Dealing with regression towards the mean
Suppose I have a 6 week weight-loss program, that I know is only effective in a fraction of the population. I weight the participants at baseline, after 1 week and after the full 6 weeks.
$$
T_0 = ...
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Why is linear regression overestimating small values and underestimating big values?
I am trying to predict age from a couple of variables using linear regression, but when I plot predicted age against real age, I can see that small values are significantly overestimated and big ...
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Backwards stepwise regression, collinearity and regression to the mean
My research paper was recently rejected and some of the feedback I received was in relation to the statistical tests done/not done. I would like help in clarifying what I could do differently as the ...
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"Regression" versus "regression to the mean" [duplicate]
Are The two concepts really two sides of the same coin ? The latter is often referred to simply as a regression, but surely this is just an unfortunate coincidence?
The former is about predicting ...
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Reconciling regression to the mean with the independence of with-replacement sampling
Say we monitor a ski jumper's consecutive jumps (distance jumped), and we assume it is a combination (sum) of the skier's skills, + luck (modelled by a random variable). We also assume that the ...
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Distinguishing responders and non-responders in studies of classical conditioning
I am concerned about the way "response" to certain experimental manipulations in psychology is defined and then used to claim that a specific subject did or did not "respond" to justify exclusion of "...
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Regression to the mean: multiple predictors
Let's say I want to predict the value of Y using the value on my predictor X. X is correlated with Y with some strength $r$ (let's say 0.5). In order to correct for regression towards the mean I ...
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Regression to the mean vs gambler's fallacy
On the one hand, I have the regression to the mean and on the other hand I have the gambler´s fallacy.
Gambler’s fallacy is defined by Miller and Sanjurjo (2019) as “the mistaken belief that random ...
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