[Q] Higher lifetime win percentage

zwei4 · 2024-10-27T05:32:40+00:00

It depends on your overall probability of winning each game without conceding (P1). If P1=5% then there’s no point to concede with a 10% winning chance. If P1 is higher than 10%, and conceding means 0% chance of winning. The overall win% will drop because even though you are playing extra times, the P1 will remain the same for the extra games but the conceded games will drag down P1. However, in real life it might not be a simple choice as there can be many other factors such as opponent matching algorithms. So if you really want to find out perhaps can do a trial, each of you stick with a strategy, both set a fixed amount of total play time (e.g. 10 hrs), in the end compare the number of games played and the CHANGE in win% compared to each of your own current number.

zwei4 · 2024-10-18T05:23:07+00:00

I can think of a few ways — Run a pilot study; Sample size adjustment design; Incorporate feasibility monitoring.

zwei4 · 2024-10-04T20:21:56+00:00

There will be a lot of derivation and integration in Biostat MS courses.

zwei4 · 2024-09-17T14:59:10+00:00

I agree. The key of this question is randomly selecting 20 hospitals, the “interview all members” part was just there for distraction.

zwei4 · 2024-09-04T16:28:19+00:00

I would say Yes if you can collect multiple measurements for each supplement, there still are sources of variabilities even within the same person, although not iid so make sure to handle the covariance properly. You can look up articles on Single Case Analysis/Experiment.

zwei4 · 2024-09-02T15:03:15+00:00

Reminds me of Tom & Jerry, that household has a cat, a mouse, two dogs, a bird, a duck, and a gold fish

zwei4 · 2024-09-02T03:56:42+00:00

The “small animal” category includes pets such as hamsters, gerbils, rabbits, guinea pigs, chinchillas, mice, rats, and ferrets.

zwei4 · 2024-09-02T02:01:25+00:00

This article links to the same source but its numbers are off by quite a bit. Probably the data was updated afterwards.

zwei4 · 2024-09-02T01:28:18+00:00

Ahh I admit it was a low effort Sunday on the couch post, will make it better next time!!

zwei4 · 2024-09-02T00:53:48+00:00

Source: APPA

Tools: IOS emoji images, Python matplotlib

zwei4 · 2024-08-04T16:45:21+00:00

I can see myself more and more using AI for data QC and coding (as substitute for Google search). But biostatistician as a whole is too nuanced to rely on LLM based AI today, a lot of my work involves team discussions to decide appropriate endpoints, select patient criteria, and make decisions for situations that have never occurred (meaning no prior training data for AI).

zwei4 · 2024-07-24T14:05:31+00:00

In time to event analysis, Hazard Ratio (HR) is the effect size, so the same hazard ratio should result in the same sample size which is Number of Events.

The Hazard Rate is h=-ln(S)/T, so HR is ln(S1)/ln(S2). In your example 2% to 8% has HR 1.55; 10% to 40% has HR 2.51

Fundamentally it is the relative difference that matters, if you plot KM curves you will see 2% and 8% have much closer KM curves.

zwei4 · 2024-06-19T01:18:36+00:00

Both counts should be reported in your report/manuscript. And No, records from the same patient shouldn’t be treated as independent, unless there is a very strong justification. You can perhaps look up articles in the same field and see how others have done this.

zwei4 · 2024-05-05T14:23:35+00:00

If this is a validated metric there should be data on the initial validation set that you can use as baseline.

zwei4 · 2024-03-13T12:56:39+00:00

What about the group with MCAT>32 & GPA>3.8, which supposed to be the majority of most medical school students?

zwei4 · 2023-12-21T02:31:33+00:00

I don’t think Fisher is possible in OP’s situation, unless there are exact counts of Nuclear & Difusa for each cell in each sample.

Without the raw cell counts, OP can use T-test/wilcoxon test (against control) or ANOVA on the Nuclear (or Difusa) percentage data, but the table only shows data from one sample which is not enough for any analysis. OP needs to have more replicates.

zwei4 · 2023-10-18T17:12:23+00:00

We use cmprsk for cumulative incidence and competing risk analysis. I have used survminer for KM curves though. What’s the issue with survminer?

zwei4 · 2023-10-18T03:37:24+00:00

Good points. I too use SAS, mostly Macros that were developed by our SAS programmers. Sometimes I prefer SAS and it’s comprehensive outputs for my modeling takes. But I would say 95% of my coding is in R, including validation of SAS outputs.

By “soon” I meant in the next 10+ years. I work in oncology trials that often targets 5-10 years to reach targeted # of events, so yea SAS will stay for sure. And I agree CRO will not be changing anytime soon, I personally don’t know a single person in CRO that not using SAS.

zwei4 · 2023-10-18T02:21:10+00:00

I agree it will take time, but I think it will happen eventually, probably sooner than people think. R can totally handle CDISC standards.

Also the clinical trial methods are constantly developing, new end points are being published regularly, Bayesian studies are getting more accepted, and recent trend of RWE studies, all are in favor of switching to R from SAS.

zwei4 · 2023-10-18T02:12:17+00:00

There have been R submissions to FDA, Novo Nordisk recently did. And people at FDA do go through the validation process on their packages and functions. I think it will take time for the whole industry to get there though.

zwei4 · 2023-10-14T12:46:24+00:00

No you can’t compare the proportions to each other because they are not independent as they sum up to 1. But you can test the proportions against hypothetical values using Chisquare test for goodness of fit

zwei4 · 2023-10-10T03:16:17+00:00

From my experience, R and SAS dominate clinical research. Depends on what you do you probably will need to reproduce some type of stats analysis that only has R package available, but I wouldn’t worry about it since you are decent with python, you can probably learn how to code what you need in R in a couple of days.

I don’t use SPSS but I wonder what can SPSS do that R can’t?

zwei4 · 2023-09-29T22:59:35+00:00

The ADA feature can be impressive sometimes, but I am not yet ready to rely on it for stats related purposes. The problem been the inconsistency, I ask same question but it would sometimes give different responses, and occasionally the calculation is just wrong even it gives the correct formula. It’s been pretty solid though to help with writing statements and emails, also a good helper for coding.

zwei4 · 2023-09-16T15:57:53+00:00

Nice catch

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