08-27-2021
pdortho
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Latest posts by pdortho
Subject Views Posted 751 01-27-2021 11:46 AM 790 01-26-2021 08:19 PM 2385 01-25-2021 12:03 PM 2413 01-24-2021 03:37 PM -
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- Posted Re: Random _residual_ (was Re: Specifying Random Effects) on Statistical Procedures. 01-27-2021 11:46 AM
- Posted Re: Random _residual_ (was Re: Specifying Random Effects) on Statistical Procedures. 01-26-2021 08:19 PM
- Posted Re: Specifying Random Effects on Statistical Procedures. 01-25-2021 12:03 PM
- Posted Re: Specifying Random Effects on Statistical Procedures. 01-24-2021 03:37 PM
01-27-2021
11:46 AM
There are 3 years of data. 7,488 out of 12,126 surgeons have data for all 3 years. I believe 700 was a typo in the previous post. 123,728 out of 726,597 patients had more than 1 surgery. Best regards, Patrick
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01-26-2021
08:19 PM
I think I left out an important bit of information, so I want to get your thoughts on if this would change how the model is specified. The observational unit is individual patients in our model, rather than surgeons. We are looking at 90-day hospital readmission after surgery for patients who are nested within surgeons, and surgeons may or may not work at more than one hospital. So, would we even need year as a repeated measure since we are not repeatedly measuring individual patient outcomes from year to year? Does year even need to be a random effect at all, since I cannot imagine patients operated on in 2018 would necessarily be more similar to each other than they are to patients operated on in 2019? The last wrinkle in all of this is how to handle patients. Most patients only appear in the dataset once, for a single surgery. However, some people can appear in the data twice if they have a second contralateral surgery. Should patient be a repeated effect then since some could have had multiple surgeries? Thanks everyone for your responses. Patrick
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01-25-2021
12:03 PM
That makes sense that year is a repeated effect. You are correct that surgeons will only have privileges in one region. I am glad we can use pseudo-likelihood as well, since that should run faster with our large dataset. We will give this model a try. Thanks again for your response. You have helped us out a great deal. Best regards, Patrick
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01-24-2021
03:37 PM
Thanks for your response to the first post Steve. I am working on that same project with the original poster, and we are both new to multi-level modeling, so your response has been very helpful to us. I have a few follow up questions about our random effects specification. We are working with a large health care claims database. We are measuring the same hospitals within each region every year. How should we handle year in the random statement, given that the same hospitals are measured in each year? I have a similar question regarding the surgeon variable. For the most part, surgeons are nested within hospitals, although some surgeons perform procedures at more than one hospital. So, would we have to specify surgeons the same way as year, since they are not completely nested within hospitals? Thanks again for your help! -Patrick
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