Description Usage Arguments Details Value Examples
This is the main access point for using parallel processing to complete numerous Cox regressions simultaneously.
1 |
proteins |
This is the vector of all proteins to be considered for Uniprotein, Adjusted Cox Regressions. |
data |
This is the tibble dataframe with the covariates for regression |
time |
This is a character vector of the Survival time to event Outcome. |
outc |
This is a character vector of the Survival event indicator Outcome. |
adjust |
This is a vector of all the adjustment variables. |
.src |
This is an indicator of whether the models are the derivation or validation models. It is 1 when the data is the derivation dataset, and 2 when it is the validation dataset. |
This function utilizes the furrr::future_map()
function to complete many
regressions quickly. Each protein is regressed individually against the time
and outcome variable specified, while adjusted for the provided variables.
The .src input is specified to distinguish data between derivation data and
validation data. Derivation data should be .src = 1
while validation
data should be .src = 2
.
a Tibble containing the results of the multiple regression models.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ## Not run:
data <- haven::read_dta('~/proteomics/studydata.dta') %>% ...
(merge study data with SomaData, see [get.visit()] for specifics)
univariate.results <- cox.arry(labels$term, data,
time = "fuptime",
outc = "hfdiag",
adjust = adjust,
.src = 1)
validation.results <- cox.arry(labels$term, data.validation,
time = "fuptime",
outc = "hfdiag",
adjust = adjust,
.src = 2)
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.