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Minimise combined RMSE
I current have a model with four free parameters that predicts the structure of ocean current velocity against depth for two components simultaneously.
The shape of each component is controlled by ...
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1answer
85 views
fastbw with rule=“p” in R's rms package: why do results depend on number of covariates?
I've been trying to use the fastbw function from the rms package in R to perform logistic regression with backward selection, with p-values as exclusion criterion (I am well aware of the arguments ...
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Computing c-index for an external validation of a Cox PH model with R
First off, I'll state that I'm aware many questions get asked about the c-index. I've searched this site and others, and I haven't found an answer for my situation. I can successfully use ...
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1answer
151 views
Best method to validate a multiply imputed Cox model with R?
This question is with regards to using a test data set to validate an imputed Cox model using R. With a non-imputed data set I would use val.surv() from ...
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1answer
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Using multiple imputation for Cox proportional hazards, then validating with rms package?
I've been researching the mice package, and I haven't yet discovered a way to use the multiple imputations to make a Cox model, then validate that model with the rms package's ...
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1answer
89 views
Does good calibration surpass roughly met assumptions and mediocre discrimination?
My question arises from my current task to develop a clinical prediction model using ordinal logistic regression (with rms), but applies to any kind of regression analysis.
The proportional odds ...
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2answers
722 views
Cross validation and ordinal logistic regression
I am trying to understand cross-validation for ordinal logistic regression. The aim of the game is to validate the model used in an analysis...
I first construct a toy data set:
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