use_cv_coxglmnet.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/use_cv_coxglmnet.R
\name{use_cv_coxglmnet}
\alias{use_cv_coxglmnet}
\title{Penalized Cox Regression With Nested CV}
\usage{
use_cv_coxglmnet(
  summarized_experiment,
  model_matrix = NULL,
  variables = NULL,
  add_survival = T,
  stratify = T,
  alpha = 0.5,
  time_to_event = "days_to_death",
  time_follow_censor = "days_to_last_follow_up",
  event = "vital_status",
  parallel = T,
  k_outer_loop = 10,
  k_inner_loop = 5,
  seed = 12,
  verbose = F,
  time_surv = NULL,
  ...
)
}
\arguments{
\item{summarized_experiment}{A SummarizedExperiment object}

\item{add_survival}{Logical - add columns to data for survival anaylsis}

\item{stratify}{Logical - stratify events in folds?}

\item{time_to_event}{Character - column name of time to the event (e.g. death, relapse)}

\item{time_follow_censor}{Character - column name of time of last follow up or right censoring}

\item{event}{Character - column name of event (vital_status)}

\item{seed}{Integer - Number for set.seed}

\item{verbose}{Logical - state progress}

\item{time_surv}{Numeric - Time of survival to calculate cauc (needs to be on the same scale)}

\item{...}{Parameters for glmnet}

\item{vari/bles}{Character Vector - column names of used variables}
}
\value{
Returns either a SummarizedExperiment or a data frame with 2 additional columns in colData (time, event). May have fewer rows because of missing data.
}
\description{
This function calulates penalized cox regression with nested cross validation
}
\details{
If no model_matrix is omitted you can hand over column names of which a model matrix is created from. Either model_matrix or variables must not be NULL. Addionally you need to specify the column names for mmRmeta::add_coldata_survival
if add_survival == TRUE.
}