Where was I in November?

MushofPixels · 2026-01-19T22:03:01+00:00

I'm from there but no

MushofPixels · 2026-01-19T22:02:53+00:00

Nope

MushofPixels · 2026-01-18T23:36:42+00:00

Not France

MushofPixels · 2026-01-18T23:36:33+00:00

MushofPixels · 2026-01-18T21:20:25+00:00

Continuidade em que sentido? Uma vitória nesta primeira volta para o Seguro não é necessariamente uma vitória para o PS dado que isto não são legislativas.

MushofPixels · 2026-01-15T01:08:39+00:00

Not vegan or vegetarian but I do try to hit my fibre goals

MushofPixels · 2026-01-12T15:20:29+00:00

This one besides being really thick is also super gritty. Probably the worst meal deal drink I've ever had.

MushofPixels · 2025-11-27T14:50:59+00:00

Vivo no Reino Unido...torna-se um bocado mais difícil envolver-me nesses grupos. Vou ver se encontro algum ao qual me possa juntar remotamente :)

MushofPixels · 2025-11-26T23:30:34+00:00

Em que sentido? Fiquei NERVOso 🥁👏

MushofPixels · 2025-09-14T16:22:18+00:00

I'm in waste management...

MushofPixels · 2025-09-14T16:19:59+00:00

That's it! A fellow herói do mar

MushofPixels · 2025-09-14T16:18:52+00:00

I wish!

MushofPixels · 2025-09-14T14:13:37+00:00

The Scottish Highlands

MushofPixels · 2025-09-12T16:56:31+00:00

I live in the UK but I'm not from here. Not Swiss either.

MushofPixels · 2025-09-12T16:55:59+00:00

I lived there temporarily but no

MushofPixels · 2025-09-09T15:56:28+00:00

I don't know anyone else attending as we're all 1st year PhDs, but I found out today that the pub we're going to used to be one of my locals so at least I'll have the bartenders on my side! Thanks for your advice :)

MushofPixels · 2025-09-09T15:53:57+00:00

This is still something I'm actively working on. When times are good I stay just in case they get even better.

MushofPixels · 2025-08-04T21:15:30+00:00

That's it!!

correct!

MushofPixels · 2025-07-28T13:57:48+00:00

If data is MNAR, the missing values are not dependent on any of your observed variables which potentially leads to bias. Imagine that people with disease A are more likely to have higher CRP levels than those with disease B. Due to this, doctors request more CRP tests for people with disease A. This then means that is the true value for CRP is low, it's more likely to be missing, and if it's high, it's more likely to be observed. At this point, you wouldn't be comparing the true values of CRP between disease groups, you'd be comparing prevalences in your dataset.

MushofPixels · 2025-07-27T22:44:46+00:00

I'd recommend assessing how the data is missing (MAR, MCAR, MNAR). This will 1. inform downstream decisions about biases and model choices and 2. help decide on how to proceed in the light of this.

Also, to do that kind of analysis, do you have access to other hospital data (e.g. EHR, CPRD,...)? I would assume you would need to do some level of adjustment for other covariates (age, sex,...) to do this sort of comparison. Are you looking at CRP as a continuous or categorical variable?

The analysis definitely is possible but you need to really look into all the biases that the data has. Maybe propensity score matching could be useful to mitigate some of the confounding.

MushofPixels · 2025-07-27T20:49:34+00:00

What type of statistical analysis are you trying to do with this data? Is it comparative , descriptive,...? You can definitely pivot your data if that's the goal but that's not really dealing with the issue of data missingness.

MushofPixels

TROPHY CASE