# Search results

1. ### Rep and Seq

Thanks! Times parameter worked as you suggested.
2. ### Rep and Seq

Was tinkering with rep and seq today and wondering about the following: > rep(c(5,12,13), each=2) [1] 5 5 12 12 13 13 I wondered what would happen if I specified seq(1:3) for each=... I assumed this would happen: 5, 12, 12, 13, 13, 13 but instead got: > rep(c(5,12,13), each=c(seq(1:3...
3. ### Paired t-test equivalent for non-normal, heteroscedastic data

Mann-Whitney U test (Mann-Whitney-Wilcoxon) is the same as the Wilcoxon rank-sum test; these are for unpaired samples. The Wilcoxon signed rank test is for paired samples. Not sure if the terminology was causing confusion.
4. ### Let's play ... "Guess the y-axis!"

A put option where the mystery metric is the price of the underlying. For the bottom graphic. Not gonna lie, didn't read it all.
5. ### Interesting (non-research) Statistics Articles

https://amstat.tandfonline.com/doi/full/10.1080/01621459.2018.1537912
6. ### Interim Analysis

I think so which is where the issue of multiplicity arises in Frequentist approaches (or even people who literally keep collecting data to achieve a low p-value). Frank Harrell mentions that this is an advantage of Bayesian approaches because it's just updating without the multiplicity issue...
7. ### Interim Analysis

A prevalent viewpoint I have encountered (often explicitly as well as implicitly while talking with people), and it becomes more dangerous (than it is) when coupled with a misunderstanding of p-values and multiplicity (especially without a priori subject matter expertise).
8. ### Overlapping confidence intervals and p values

I suppose if I wasnt lazy, and then extended to a nonzero null case, I would have provided the same conclusion since any numbers contained within one interval are fail to reject the null for those numbers. Thanks for the clarity!
9. ### Overlapping confidence intervals and p values

In the case of overlapping confidence intervals for A and B: -if the point estimate of A is within the CI of B, then nonsignificant at the complementary alpha level for the null of equality - if the point estimate of A is outside of the CI of B, this would be significant at the complementary...
10. ### Help with statistical analysis for physio research

Krippendorff's alpha would also be useful to look at systematic disagreement or agreement among the replies. It also has better desirable properties for investigating "agreement", but as @Miner said, some simpler methods like a Bland-Altman plot might be useful and even just looking at the...
11. ### Likert scales

TO: DarioMarenelli This is why we ask questions... Finding them on EFA doesn't make them real, they very well can be spurious covariance structures, so context is needed, even in exploratory. Give some examples of statistical analyses that don't need context. You also used ad hominems on...
12. ### Likert scales

@Karabiner asked fair questions. Typically people conflate Likert items and scales and most people who think they're using these are actually using Likert-type items/scales because they don't meet the theoretical requirements of true Likert items/scales. Getting defensive about your knowledge...
13. ### Residual sum of square

This is, as @hlsmith said, a moot point. It's illogical to compare models with different dependent variables, generally speaking. Weight in grams is a different DV than weight in kg (even though it is a transformation), and only RSS should be compared from the same DV, but even this is missing...
14. ### Bonferoni test

What do you believe "significance" means?
15. ### Bonferoni test

This is a pretty useless thing to explain, in general. P-values have limited information to convey and it's a misconception that "significance" is some targeted endpoint with tons of value. It also sounds like in your OP that your goal is to have something be significant since your concern is...
16. ### Bonferoni test

Just reposting this because anyone who reads now in the future should see the emphasis that p-values tell you nothing about "A is quite better than B."
17. ### Comparing withdrawal rates for a course

I'd probably also look for a CI method that preserves the nominal coverage. For a difference in two proportions, I believe the Agresti-Caffo method is a good option and if just trying to get a CI for each proportion, then the Agresti-Coull method is a good choice (but there are others with...
18. ### Confidence interval in inter-rater reliability

Depends on the underlying sampling distribution...if it's asymmetric, you get an asymmetric CI.
19. ### Omitted variable bias

1) I disagree here, and Harrell makes a case for this when he points out that if you dichotomize a continuous independent variable, you can reduce confounding by also including the original continuous variable. 3) I assuming linearity, it wouldn't look different than a two variable interaction...
20. ### Omitted variable bias

I think confounding and OVB at least can be the same, if they are not always the same. The first example I learned about a fractional factorial experimental design, the guy teaching it (PhD in Stats from a good program along with decades of consulting), he explained a fractional factorial as...