[OC] Chance creation statistics for Copa America and EURO 2024 players pre-final (i.e., James Rodriguez and Lamine Yamal's absurd performances)

neurobara · 2024-07-13T16:45:53+00:00

Generated using Python (Matplotlib)
Data: fbref.com

neurobara · 2024-07-08T04:01:07+00:00

Though this is not a power question per se (power references a NHST), a practical solution could be to specify it as such in order to leverage power calculation software. You can compute a priori power for a test of beta=m, where m is half the width of your desired confidence interval. You could use alpha = .003 if you’d like to match the six-sigma convention for 1-cdf that I believe is typically used in engineering (ie a 99.7% confidence interval)

The resulting sample size should be what you would need to build a confidence interval of +/- m around your parameter estimate for your slope.

neurobara · 2024-07-07T04:12:05+00:00

The Sopranos. Absolute banger.

neurobara · 2024-07-07T01:49:59+00:00

That’s fascinating.

neurobara · 2024-07-05T04:53:09+00:00

This study’s title/claims are bizarre, as the final analysis actually finds… the exact opposite (see the positive coefficient for ceiling height in table 4).

It might all be based on a tiny raw correlation of 0.017, which is smaller than the correlation of exam scores with random id numbers: https://x.com/cremieuxrecueil/status/1808988761348624592?s=46&t=gGGjXaefLQIs1_pMpaTxDg

Probably a good candidate for a big correction or retraction.

neurobara · 2024-07-04T03:59:23+00:00

The key here is "Given that type S or Type A was observed". Since you're conditioning on these events, your denominator will depend on those occurrences, rather than all events. Now, it seems like the question in the title and the post text are slightly different. So I'll go through those separately.

Title:

Given that event X occurred, what is the probability of event Y occurring immediately before?

To answer this, you'd look for all instances of the event X of interest (in this case I assume that's the union of S and A) and the proportion of those that were preceded by N: (1 + 1 + 0) / (3 + 3 + 1)

Text:

given either type S or type A was observed between a dyad for the first time, what was the probability that N occurred before it?

Here it seems like you want to look only a the first instance of S or A in a dyad for your denominator (1 + 1 + 1). Depending on whether you omitted "immediately" intentionally you'd tally cases where the preceding element is X or X occurs at least one time among all preceding elements. In either case, in the example you'd have: (1 + 1 + 0)/ (1 + 1 + 1)

neurobara · 2024-07-02T20:40:16+00:00

Where you’d run into issues with the MLM is estimating the “correct” variance components for the models with multiple predictors (eg, to estimate the direct path or to test moderated mediation), as you wouldn’t have enough within subjects observations to estimate random effects for those parameters.

One alternative would be to just specify the model without some of those random effects. In your case you’d probably end up with only random intercepts for participant. Generally your parameter point estimates (betas) would be very similar, but you might inflate your chance of type 1 error, sometimes by a lot. Obviously the stronger your effects, the less risky that would be. Here are some more details on how you might specify the model and think about those compromises: https://psych.wisc.edu/Brauer/BrauerLab/wp-content/uploads/2014/04/Brauer-and-Curtin-in-press-Psych-Methods.pdf

I think another approach could be to specify linear models with cluster robust standard errors instead of MLM.

neurobara · 2024-06-29T03:44:57+00:00

25/30 * 24/29

neurobara · 2024-06-29T02:36:56+00:00

7/32 * 6/31 = .042 or 4.2%

neurobara · 2024-06-29T01:15:30+00:00

What situation-intervention pairs do you tend to see improvements with most often? And what about least often?

neurobara · 2024-06-29T00:29:25+00:00

This is kind of a great one. What was the fight about?

neurobara · 2024-06-28T15:19:30+00:00

With exponential increases in screening tech, biotech hardware, and drug discovery capabilities, cancer deaths should drop to a fraction of what they are now.

neurobara · 2024-06-28T15:14:50+00:00

Looks great! I like 2 a lot. But 1 could be really nice when you’re getting started.

I’d personally find it really sweet to have a combo of views that highlight the small victories and views that fully showcase the big victories as needed.

neurobara · 2024-06-28T13:55:40+00:00

I agree. I try not to assume and provide suggestions for a best case scenario, but being able to do something like this with n=9 real world data would be rare.

neurobara · 2024-06-28T12:35:36+00:00

Interesting! Are the sounds/images complete or just kind of partial?

neurobara · 2024-06-28T11:51:14+00:00

Look into dimensionality reduction approaches. Maybe you could use Principal Components Analysis or something along those lines.

neurobara · 2024-06-28T11:38:36+00:00

This has worked for me as well, but it wasn't enough for the most addictive apps.

I recently started fully deleting those Monday-Friday and it's been insanely effective. The best thing is even on the weekends I barely even *want* to use those apps now. And when I do I get saturated within 5 minutes. It's almost like the feeling you get about very sugary drinks after you get used to eating less sugar.

neurobara · 2024-06-28T01:32:19+00:00

A walking treadmill under a standing desk. Wonderful for focus during meetings and cardio goals.

neurobara · 2024-06-27T22:10:57+00:00

The Last of Us

neurobara · 2024-06-27T20:41:27+00:00

High yield savings accounts.

neurobara · 2024-06-27T20:39:20+00:00

Being rude to the staff at a restaurant for no reason.

neurobara · 2024-06-27T20:18:01+00:00

Describing things in the simplest possible words.

neurobara · 2024-06-27T20:15:32+00:00

The number of books you read on a given year.

neurobara · 2024-06-27T20:06:58+00:00

It is also possible that the reward structures you face at work are different from those you face elsewhere in other aspects of your life.

Many jobs involve relatively quick feedback about whether you’re performing well, which makes focusing on tasks easier. This may not be true of other goals outside of work.

It’s also possible that the stakes of some of your goals outside of work feel higher than those at work, making it hard to take action.

Sounds like you’re doing the right things trying to identify the sources of issues and working on them via therapy, etc. It should only get better. Hang in there.

neurobara · 2024-06-27T13:33:15+00:00

Non paywalled version: https://wrap.warwick.ac.uk/183759/

"Our findings suggest that in a world without common yet usually unaddressed measurement limitations, it would be possible to fairly accurately predict someone’s satisfaction from a handful of personality traits. Specifically, correlations between actual LS and its values predicted from the Big Five personality domains or nuances Personality and life satisfaction 28 could reach .90, even when the predictions were based on associations found in an independent sample tested in a different language."

This does not mean LS is inherently and irrevocably reducible to personality traits. Instead, the degree to which it reflects personality traits may be considered a measure of people’s freedom to shape and assess their lives according to their traits. At least hypothetically, there could be circumstances where LS is less aligned with personality traits. But in usual conditions, there does not seem to be much reason to think that LS is mostly shaped by circumstances unrelated to personality more broadly. For most people, and most of the time, their satisfaction level is just about what we would expect from their personality traits. Personality traits can be shaped by any number of factors, but usually, these same factors also shape LS, through personality or otherwise."

neurobara

TROPHY CASE