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 # Functions to Run Cure Models (Once or Multiple Times) ------------------------
 # ------------------------------------------------------------------------------
 
-source(here::here("R", "clean-model-results.R"))
 
 # Single Model Run -------------------------------------------------------------
 # Wrapper function for smcure to accept multi-level variables and save necessary 
@@ -96,6 +95,8 @@ multiple_mod_runs <- function(formula,
                               num_repeats = 10, 
                               data = mel) {
 
+  source(here::here("R", "clean-model-results.R"))
+
   # pull original variables from formula
   mf <- formula
   mf <- eval(mf, parent.frame())
@@ -235,28 +236,4 @@ multiple_mod_runs <- function(formula,
 }
 
 
-# Examples
-
-# data <- ISwR::melanom %>%
-#   mutate(status = case_when(status %in% c(1, 3) ~ 1, 
-#                             TRUE ~ 0)) %>%
-#   mutate(sex = case_when(sex == 2 ~ "male", 
-#                          sex == 1 ~ "female"),
-#          ulc = case_when(ulc == 1 ~ "present", 
-#                          ulc == 2 ~ "absent"))
-# 
-# formula <- Surv(days, status) ~ ulc + sex
-#   
-# x <- multiple_mod_runs(formula,
-#                               nboot = 200,
-#                               eps = 0.0001, 
-#                               num_repeats = 3, 
-#                               data = data)
-# x$model_results
-# 
-# x$var_surv_stab
-# x$p_surv_stab
-# 
-# x$var_cure_stab
-# x$p_cure_stab
 

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+
+# Clean Model Results ----------------------------------------------------------
+mmcure <- function(fit_k2_cat) {
+  enframe(fit_k2_cat$b) %>% 
+  left_join(enframe(fit_k2_cat$b_pvalue),
+            by = "name") %>%
+  transmute(name, 
+            value = round(exp(value.x), 2), 
+            pvalue = round(value.y, 2))
+}
+
+mmsurv <- function(fit_k2_cat) {
+  enframe(fit_k2_cat$beta) %>% 
+  left_join(enframe(fit_k2_cat$beta_pvalue), by = "name") %>%
+  transmute(name, 
+            value = round(exp(value.x), 2), 
+            pvalue = round(value.y, 2))
+}

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.Rproj.user/A70D84A5/sources/s-D23FE8C5/91B9DCD1-contents

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+---
+output: github_document
+---
+
+<!-- README.md is generated from README.Rmd. Please edit that file -->
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>",
+  fig.path = "man/figures/README-",
+  out.width = "100%"
+)
+```
+
+# Cure Model Pipeline
+
+<!-- badges: start -->
+<!-- badges: end -->
+
+The goal of this package is to provide an easy way to build, evaluate and visualize mixture cure models ([link to paper draft](https://docs.google.com/document/d/1Lhom9H7Hxb8_C6d55Trs9JHSfJCn1i6yuu_xsDyYqZQ/edit?usp=sharing))
+
+
+## Available Functions
+
+- `fit_cure()` - wrapper for `smcure::smcure()` function that allows you to pass multilevel variables as factors directly (instead of first creating dummy codes). It also saves outputs necessary to create nomogram.
+- `nomogram()-` - accepts an object created by `fit_cure()` and creates graphical nomogram based on model fit
+- `cure_calibration()` - accepts an object created by `fit_cure()` and creates a calibration curve for uncured patients
+- `multiple_mod_runs()`- allows you to check stability of models but running them multiple times and viewing distributions of variables and p-values. 
+- Coming soon:
+  - k-index and C-index wrapper functions
+  - tidyr function to better clean/view coefficients from cure model
+
+## Example 
+
+```{r, eval = FALSE}
+library(smcure)
+library(ISwR)
+library(gtsummary)
+library(tidyverse)
+
+# Prepare Data --------------------------
+mel <- ISwR::melanom %>%
+  mutate(status = case_when(status %in% c(1, 3) ~ 1, 
+                            TRUE ~ 0)) %>%
+  mutate(thick_cat = 
+              case_when(thick <= 129 ~ "≤ 129", 
+                        thick <= 322 ~ "less equal 322", 
+                        thick > 322 ~ "greater 322")) %>%
+  mutate(thick_cat = fct_relevel(thick_cat, "≤ 129", "≤ 322")) %>%
+  mutate(sex = case_when(sex == 2 ~ "male", 
+                         sex == 1 ~ "female"),
+         ulc = case_when(ulc == 1 ~ "present", 
+                         ulc == 2 ~ "absent"))
+
+# Run Pipeline --------------------------
+fit <- fit_cure(formula = Surv(days, status) ~ ulc + sex + thick_cat + thick ,
+                data = mel)
+cure_nomogram(fit, prediction_time = 300)
+cure_calibration(fit, prediction_time = 300)
+
+
+# Check Stability ----
+formula <- Surv(days, status) ~ ulc + sex
+x <- multiple_mod_runs(formula,
+                              nboot = 200,
+                              eps = 0.0001,
+                              num_repeats = 3,
+                              data = mel)
+x$model_results
+
+x$var_surv_stab
+x$p_surv_stab
+
+x$var_cure_stab
+x$p_cure_stab
+
+```
+
+

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+# ignore R data files
+.Rproj.user
+.Rhistory
+.RData
+.rds
+.Ruserdata
+.Rapp.history
+.Rhistory.RData
+
+# Temporary files created by R markdown
+*.utf8.md
+*.knit.md
+
+# ignore other types of data files
+*.xlsx
+*.xls
+*.csv
+*.dta
+*.sas7bdat
+*.sav
+*.txt
+
+# ignore data folder/symbolic link/sensitive file
+data
+admin
+raw-data
+secure_data
+ext_data
+tmp
+env.json
+archives
+outputs/archive
+
+# OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3
+.httr-oauth
+
+# ignore misc files
+~$*.docx
+~$*.xlsx
+~$*.pptx
+~$*.tmp
+Thumbs.db
+.DS_Store

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