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Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

13 votes
Accepted

Can (some) linear regression model this (population) function accurately?

The authors should have written ...it will not be possible to produce an accurate estimate using simple linear regression. ...where simple linear regression means using a single predictor: only $X_1$ … You are right that in this same paragraph, the authors had been discussing (multiple) linear regression in general: For example, linear regression assumes that there is a linear relationship between $ …
civilstat's user avatar
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10 votes
Accepted

What is special about the Poisson/Binomial distributions such that they have special regress...

There are also Beta regression (Y = proportions between 0 and 1), as well as Exponential, Gamma, and Weibull regressions (Y = waiting times or survival times, though a course on survival analysis might … As @JeremyMiles mentions in a comment, there's also Negative Binomial regression (Y = number of failures until a certain number of successes). …
civilstat's user avatar
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10 votes
Accepted

Is multicollinearity a "warning sign" for causal inference?

Is multicollinearity a "warning sign" for causal inference? It can be. I agree with you that there are plenty of legitimate concerns with multicollinearity, including the ones you raised. And they c …
civilstat's user avatar
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1 vote

Interpreting sub-sample analysis when coefficient signs are opposite

The interpretation depends strongly on exactly what your actual variables are and how your study was designed. In my experience, Simpson's Paradox usually happens with observational data, where the "t …
civilstat's user avatar
  • 4,603
31 votes
Accepted

Why do we need multivariate regression (as opposed to a bunch of univariate regressions)?

Be sure to read the full example on the UCLA site that you linked. Regarding 1: Using a multivariate model helps you (formally, inferentially) compare coefficients across outcomes. In that linked exam …
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11 votes

Why is lambda "within one standard error from the minimum" is a recommended value for lambda...

This is Breiman, Friedman, Stone, and Olshen's Classification and Regression Trees (1984). They "derive" this rule in section 3.4.3. …
civilstat's user avatar
  • 4,603
5 votes

Can I perform logistic regression or any other type of regression on this dataset?

Then it may be possible to fit & interpret a logistic regression. …
civilstat's user avatar
  • 4,603
3 votes

In Bishop's textbook, is the example of overfitting exaggerated?

A polynomial of 9th order needs to have 8 bumps. That's all it needs. So Bishop's curve could simply look like the black curve which I drawn. When we eyeball a curve, we tend to draw something more …
civilstat's user avatar
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4 votes

Variance of $K$-fold cross-validation estimates as $f(K)$: what is the role of "stability"?

This answer focuses not on stability, but on a different related issue that I have not seen addressed in the answers/comments above. There is "conventional wisdom" about LOOCV having higher variance, …
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