Week 12 Assignment – 100 points Objective: Using Logistic Regression to handle a binary outcome. Given the prostate cancer dataset, in which biopsy results are given for 97 men: • You are to predict tumor spread in this dataset of 97 men who had undergone a biopsy. • The measures to be used for prediction are: age, lbph, lcp, gleason, and lpsa. This implies that binary dependent variable of lcavol will be the outcome variable. We start by loading the appropriate libraries in R: ROCR, ggplot2, and aod packages as follows: > install.packages(“ROCR”) > install.packages(“ggplot2”) > install.packages(“aod”) > library(ROCR) > library(ggplot2) > library(aod) Next, we load the csv file and check the statistical properties of the csv File as follow: > setwd(“C:/RData”) # your working directory > tumor <- read.csv(“prostate.csv”) # loading the file > str(tumor) # check the properties of the file . . . continue from here! Reference R Documentation (2016: 2024 – Do my homework – Help write my assignment online). Prostate cancer data. Retrieved from http://rafalab.github.io/pages/649/prostate.html
Integration of Genetics and Genomics into Ethical Nursing Practice
NUR3306CBE Section 01CBE Integration of Genetics and Genomics into Ethical Nursing Practice (11 Weeks) – CBE Online Course – 2024 Summer Quarter Deliverable 5 – Policy Influences on Healthcare Decisions Assignment Content 1. Competency Differentiate the legal and professional policies influencing healthcare decisions. Student Success Criteria View the grading rubric for this deliverable by selecting […]
