In AlfonsoRReyes/RepDataPeerAssessment1: Reproducible Research Assignment 1. Developed as a package

library(RepDataPeerAssessment1)
library(rprojroot)

project.data <- find_package_root_file('data')
project.extdata <- find_package_root_file('inst/extdata')
project.R <- find_package_root_file('R')
project.data
project.R
project.extdata

download.file("http://www.statsci.org/data/general/titanic.txt", paste(project.extdata, "titanic.txt", sep = "/"))

titanic <- read.table(paste(project.extdata, "titanic.txt", sep = "/"), sep = "\t", header = TRUE)
summary(titanic)

titanic0 <- titanic
save(titanic0, file = paste(project.extdata, "titanic.rda", sep = "/"))
set.seed(4321)

titanic$Sex[sample(nrow(titanic), 10)] <- NA
titanic$PClass[sample(nrow(titanic), 10)] <- NA
titanic$Survived[sample(nrow(titanic), 10)] <- NA

# percentage of missing data
colMeans(is.na(titanic))

fullglm <- glm(Survived ~ PClass + Sex + Age,
    family = binomial, data = titanic0)
summary(fullglm)

After Imposing some more Missings, the ListWise Deletion Results

fullglm <- glm(Survived ~ PClass + Sex + Age,
    family = binomial, data = titanic)
summary(fullglm)

AlfonsoRReyes/RepDataPeerAssessment1 documentation built on May 5, 2019, 4:53 a.m.