cpmt03.qmd

---
title: CPMT3
subtitle: Cox Proportional Hazards Model Tables with Separate Models for Each Covariate
categories: [CPM]
---

------------------------------------------------------------------------

::: panel-tabset
## Setup

We prepare the data in the same way as in [CPMT1](../tables/cpmt01.qmd).

```{r, message = FALSE}
library(tern)
library(dplyr)

adtte <- random.cdisc.data::cadtte %>%
  df_explicit_na() %>%
  filter(PARAMCD == "OS", BEP01FL == "Y") %>%
  mutate(
    AVAL = day2month(AVAL),
    AVALU = "Months",
    event = 1 - CNSR
  )
```

## Table

The separate Cox Proportional Hazards models for each covariate can be fitted and summarized in a table using the `summarize_coxreg()` function in `tern`.
This function takes the same `variables`, `at`, and `control` arguments that are used to fit a model using the `fit_coxreg_univar()` function - specifying the time, event and covariate in a `variables` list, and `control` and `at` with any further customizations to the model.
Note that the default confidence level is 95% but this can be customized via the `conf_level` element in `control`.

We input these three arguments into the `summarize_coxreg()` function to summarize the model fit in a table layout, and then build the table with our pre-processed `adtte` data set.

```{r}
lyt <- basic_table() %>%
  summarize_coxreg(
    variables = list(
      time = "AVAL",
      event = "event",
      covariates = c("COUNTRY", "AGE")
    )
  )

build_table(lyt = lyt, df = adtte)
```

{{< include ../misc/session_info.qmd >}}
:::