R Packages used in these notes

Here, we’ll load in the packages used in these notes.

library(tableone)
library(skimr)
library(ggridges)
library(magrittr)
library(pander)
library(arm)
library(survival)
library(OIsurv)
library(survminer)
library(rms)
library(leaps)
library(lars)
library(Epi)
library(pROC)
library(ROCR)
library(simputation)
library(modelr)
library(broom)
library(tidyverse)

skim_with(numeric = list(hist = NULL), 
          integer = list(hist = NULL), 
          ts = list(line_graph = NULL))

specify_decimal <- function(x, k) format(round(x, k), nsmall=k)

Data used in these notes

Here, we’ll load in the data sets used in these notes.

fakestroke <- read.csv("data/fakestroke.csv") %>% tbl_df
bloodbrain <- read.csv("data/bloodbrain.csv") %>% tbl_df
smartcle1 <- read.csv("data/smartcle1.csv") %>% tbl_df
bonding <- read.csv("data/bonding.csv") %>% tbl_df
cortisol <- read.csv("data/cortisol.csv") %>% tbl_df
emphysema <- read.csv("data/emphysema.csv") %>% tbl_df
prost <- read.csv("data/prost.csv") %>% tbl_df
pollution <- read.csv("data/pollution.csv") %>% tbl_df
resect <- read.csv("data/resect.csv") %>% tbl_df
colscr <- read.csv("data/screening.csv") %>% tbl_df
colscr2 <- read.csv("data/screening2.csv") %>% tbl_df
authorship <- read_csv("data/authorship.csv") 
hem <- read.csv("data/hem.csv") %>% tbl_df
leukem <- read.csv("data/leukem.csv") %>% tbl_df