/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Problem 28 A large number of surgery patien... [FREE SOLUTION] | 91影视

91影视

Log out

Learning Materials

Features

Discover

Chapter 10: Problem 28

A large number of surgery patients get infections after surgery, which can sometimes be quite serious. Researchers randomly assigned some surgery patients to receive simple antibiotic ointment after surgery, others to receive a placebo, and others to receive just cleansing with soap. If we wanted to test the association between treatment and whether patients get in infection after surgery, would this be a test of homogeneity or of independence? Explain. (Source: Hospitals Could Stop Infections by Tackling Bacteria Patients Bring In, Study Finds, New York Times, January \(6,2010 .\) )

Short Answer

Expert verified
To test the association between treatment type and occurrence of infection after surgery, a test of independence should be conducted. This test will determine whether the type of treatment affects the rate of infection after surgery, thereby asserting the relationship between the variables.

Step by step solution

01

Identify the variables

In this study, there are two categorical variables. The first variable is the type of treatment (antibiotic ointment, placebo, or cleansing with soap), and the second variable is the health outcome (whether the patient gets an infection or not after surgery).
02

Understand the relationship

The exercise asks to test if the incidence of infection is associated with the type of treatment. This indicates that the nature of the variables is such that one variable could potentially affect the other. In other words, the type of treatment (independent variable) might affect whether the patient gets an infection or not (dependent variable).
03

Choose the appropriate test

Due to the nature of the variables as reasoned above, a test of independence is more suitable than a test of homogeneity. A test of independence will check if the rate of infection is independent of the treatment type, thus providing an argument for or against the effectiveness of the treatments.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91影视!

Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Understanding Categorical Variables
In statistics, understanding the variables' nature is essential when conducting any analysis. Categorical variables represent data that can be divided into distinct categories.
They don't have a natural numerical order or ranking. In the context of our exercise on post-surgery infections, we identify two main categorical variables:
  • Treatment Type: This includes categories such as antibiotic ointment, placebo, and cleansing with soap.
  • Health Outcome: This is categorized as whether or not a patient develops an infection.
These categorical variables help organize data into groups which facilitate statistical analysis.
By correctly identifying and categorizing variables, researchers can apply appropriate statistical methods to explore relationships or effects.
Exploring Experimental Design
Experimental design is a core aspect of research methods that allows researchers to determine causal relationships between variables.
In the exercise scenario, researchers implemented an experimental design by randomizing surgery patients into different treatment groups. This random assignment plays a crucial role in ensuring that the groups are comparable at the start of the experiment.
Let's break down the key components of this experimental design:
  • Random Assignment: Patients were randomly assigned to receive one of three treatments (antibiotic ointment, placebo, cleansing with soap). This helps to eliminate bias and control for confounding variables.
  • Control Group: The placebo and soap groups can be considered as controls. This allows for comparison with the main treatment (antibiotic ointment) to assess its effectiveness.
By understanding these components, we can appreciate the careful setup that allows researchers to discern potential cause-and-effect relationships in the data.
Health Outcomes Analysis
Health outcomes analysis is a method of examining data to understand the effectiveness of medical treatments or interventions.
In this exercise, the focus is on whether patients develop infections post-surgery as a result of receiving different treatments.
Key considerations when analyzing health outcomes include:
  • Outcome Measurement: Ensures consistency in how infections are recorded, ensuring a reliable comparison between groups.
  • Associative Analysis: Uses statistical tools to determine associations between treatment types and infection rates, such as the test of independence.
The aim is to provide evidence on the efficacy of treatments 鈥� in this case, whether antibiotic ointment significantly reduces infection compared to other treatments.
By careful analysis, we can make informed conclusions about potential health outcomes.

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

According to the website MedicalNewsToday.com, coronary artery disease accounts for about \(40 \%\) of deaths in the United States. Many people believe this is due to modern-day factors such as high-calorie fast food and lack of exercise. However, a study published in the Journal of the American Medical Association in November 2009 (www.medicalnewstoday .com) reported on 16 mummies from the Egyptian National Museum of Antiquities in Cairo. The mummies were examined, and 9 of them had hardening of the arteries, which seems to suggest that hardening of the arteries is not a new problem. a. Calculate the expected number of mummies with artery disease (assuming the rate is the same as in the modern day). Then calculate the expected number of mummies without artery disease (the rest). b. Calculate the observed value of the chi-square statistic for these mummies.

In a 2018 article published in The Lancet, Kappos et al. studied the effect of the drug siponimod in treating patients with secondary progressive multiple sclerosis (SPMS) using a double-blind, randomized, controlled study. Of the 1099 patients given the drug, 198 experienced a severe adverse outcome. Of the 546 patients given the placebo, 82 experienced a severe adverse outcome. a. Find the percentage in each group that suffered a severe adverse outcome. b. Create a two-way table with the treatment labels (drug/placebo) across the top. c. Test the hypothesis that treatment and severe adverse outcome are associated using a significance level of \(0.05 .\)

In a 2016 article published in the Journal of American College Health, Heller et al. surveyed a sample of students at an urban community college. Students' ages and frequency of alcohol use per month are recorded in the following table. Because some of the expected counts are less than 5, we should combine some groups. For this question, combine the frequencies \(10-29\) days and Every day into one group. Label this group \(10+\) days and show your new table. Then test the new table to see whether there is an association between age group and alcohol use using a significance level of \(0.05\). Assume this is a random sample of students from this college. $$\begin{array}{lcccc}\hline & {\text { Alcohol Use }} \\\\\text { Age } & \text { None } & \text { 1-9 days } & \text { 10-29 days } & \text { Every day } \\ \hline 18-20 & 182 & 100 & 27 & 4 \\ \hline 21-24 & 142 & 109 & 35 & 4 \\\25-29 & 49 & 41 & 5 & 2 \\\\\hline 30+ & 76 & 32 & 8 & 2 \\ \hline\end{array}$$

You flip a coin 100 times and get 58 heads and 42 tails. Calculate the chi- square statistic by hand, showing your work, assuming the coin is fair.

According to a 2017 report, \(64 \%\) of college graduate in Illinois had student loans. Suppose a random sample of 80 college graduates in Illinois is selected and 48 of them had student loans. (Source: Lendedu.com) a. What is the observed frequency of college graduates in the sample who had student loans? b. What is the observed proportion of college graduates in the sample who had student loans? c. What is the expected number of college graduates in the sample to have student loans if \(64 \%\) is the correct rate? Do not round off.
See all solutions

Recommended explanations on Math Textbooks

Logic and Functions

Read Explanation

Discrete Mathematics

Read Explanation

Geometry

Read Explanation

Pure Maths

Read Explanation

Mechanics Maths

Read Explanation

Statistics

Read Explanation
View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.