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I have a dataset that contains approximately 95% (presumably) independent data and 5% data where more than one row is influenced by the same outside factor. I [describe it in more more detail in this …
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I'm working on a time-varying cox regression analysis.
I'm attempting to add time varying covariates to a dataset in long format, following the examples [here](https://lifelines.readthedocs.io/en/lat…
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One of the challenges in a CPH analysis is including the right features. The simplest approach consists in selecting a feature subset using univariate Cox regression. However, this approach relies on …
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https://doi.org/10.1101/131367 (http://biorxiv.org/content/early/2017/04/27/131367)
> Translating the vast data generated by genomic platforms into accurate predictions of clinical outcomes is a fu…
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Hello,
I am experiencing an issue with the `Scissor` function in Seurat while analyzing single-cell RNA-seq data. I am trying to integrate my Seurat object with Scissor for further analysis, but I …
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In theory, it would also be possible to specify the learner which is used to learn the censoring model, tune the parameters, etc.... For now I'd restrict to simple parametric learner, e.g. `coxph`, bu…
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Hello, Langzeng, I am very interested in your tdCoxSNN. There is a time-dependent in the naming of this model. I want to ask where this time-dependent is reflected? I look forward to your reply!
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There seem to be differences in how R and Stata handle failure times equal to zero (or more generally, failure times equal to entry times). We currently agree with R (at least in the failure time == …
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Let's say that some samples are grouped (patients in a hospital, etc.) and that these groupings induce correlations between the samples.
If I'm interested in understanding the effect of treatment …
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Dear prof. Harrell,
I've recently learned of a way to work with time-dependent coefficients when the proportional hazards assumption is violated in the cox-regression: By splitting the dataset using …