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Results tagged with regression
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user 17414
Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
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 …
- 4,603
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 $ …
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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. …
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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). …
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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 …
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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. …
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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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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 …
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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 …
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