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Although researchers do their best to reduce error within every study, there will always be error. It is important to identify and report any possible error within the research study in order to...

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Although researchers do their best to reduce error within every study, there will always be error. It is important to identify and report any possible error within the research study in order to accurately interpret the research study's findings. In epidemiologic research, the focus is on assessing confounding and effect modification along with normal statistical measures (p-values, confidence intervals, etc.).

For this Application Assignment, you will calculate and interpret the effects of confounding, random error, and effect modification within epidemiologic research. Read each of the following questions and answer them appropriately:

  • Consider each of the following scenarios and explain whether the variable in question is a confounder:
    1. A study of the relationship between exercise and heart attacks that is conducted among women who do not smoke. Explain whether gender is a confounder.
    2. A case-control study of the relationship between liver cirrhosis and alcohol use. In this study, smoking is associated with drinking alcohol and is a risk factor for liver cirrhosis among both non-alcoholics and alcoholics. Explain whether smoking is a confounder.
  • Interpret the results of the following studies
    1. An odds ratio of XXXXXXXXXX% confidence interval: XXXXXXXXXXis found for the association of low socioeconomic status and occurrence of obesity.
    2. A relative risk of 3.0 is reported for the association between consumption of red meat and the occurrence of colon cancer. The p-value of the association is 0.15.
    3. An odds ratio of 7 (95% confidence interval: 3.0 – 11.4) is found for the association of smoking and lung cancer.
  • The relationship between cigarette smoking and lung cancer was conducted in a case-control study with 700 cases and 425 controls. Using the results below, calculate the crude odds ratio and explain what the ratio means:
  • Heavy Smoking—Cases: 450; Controls: 200
  • Not Heavy Smoking—Cases: 250; Controls: 225
  • A case-control study looked at the association of alcohol use with the occurrence of coronary heart disease (CHD). There were 300 participants in the study (150 cases and 150 controls). Of the cases, 90 participants drank alcohol; of the controls, 60 participants drank alcohol.
    Design the appropriate 2x2 table, calculate and interpret the appropriate measure of association.
    You suspect that the association between alcohol use and CHD might be confounded by smoking. You collect the following data:
    Smokers Non-Smokers
    CHD No CHD CHD No CHD
    Alcohol Use 80 40 10 20
    No Alcohol Use 20 10 40 80

    Calculate the appropriate measure of association between alcohol use and CHD in both smokers and non-smokers. Discuss whether smoking was a confounder of the association. What is the relationship of alcohol use to CHD after controlling for confounding?
  • A study was conducted in young adults to look at the association between taking a driver's education class and the risk of being in an automobile accident. 450 participants were included in the study, 150 cases who had been in an accident and 300 controls who had not. Of the 150 cases, 70 reported having taken a driver's education class. Of the 300 controls, 170 reported having taken a driver's education class.

Calculate and interpret the appropriate measure of association between driver's education and accidents.
The question arose as to whether gender might be an effect modifier of this association. When gender was assessed, the data looked like the following:
Women Men
Accident No Accident Accident No Accident
Driver's Ed 10 50 60 120
No Driver's Ed 40 50 40 80

Perform the appropriate calculations to test for effect modification. Interpret your results.
005_ov035k-xgoufn2h.doc 005_bf435k-x1j4iahq.doc
Answered Same Day Dec 21, 2021

Solution

Robert answered on Dec 21 2021
133 Votes
Assessing Random E
or, Confounding, and Effect Modification
Although researchers do their best to reduce e
or within every study, there will always be
e
or. It is important to identify and report any possible e
or within the research study in
order to accurately interpret the research study's findings. In epidemiologic research, the
focus is on assessing confounding and effect modification along with normal statistical
measures (p-values, confidence intervals, etc.).
For this Application Assignment, you will calculate and interpret the effects of
confounding, random e
or, and effect modification within epidemiologic research. Read
each of the following questions and answer them appropriately:
ï‚· Consider each of the following scenarios and explain whether the variable in
question is a confounder:
a. A study of the relationship between exercise and heart attacks that is
conducted among women who do not smoke. Explain whether gender is a
confounder.
. A case-control study of the relationship between liver ci
hosis and alcohol
use. In this study, smoking is associated with drinking alcohol and is a risk
factor for liver ci
hosis among both non-alcoholics and alcoholics. Explain
whether smoking is a confounder.
Ans:
A confounding variable is such a variable which is related to explanatory variable and affects
the response variable. But the main problem is that the effect of a confounding variable on the
esponse variable cannot be separated from the effect of the explanatory variable on the response
variable thus we need to control the confounding variable to get the true effect of explanatory
variable on response variable.
a) As we know the rate of heart attack is not equal for Male and Females and this has been
proved by some research also (http:
www.hearthealthywomen.org/news-cente
ecent-
news/heart-attack-gender-gap-na
ows.html <--- this website is talking about such an
survey).One has higher tendency and thus higher risk of heart attack. So when we want to
check whether exercise causes to lower the rate or not we need to fix the gender 1
st
. Thus
gender is a confounder in this study.
) Here we want to see the association between liver ci
hosis and alcohol use. As we know
just like alcohol, smoking can cause some serious damages on the liver, even prior
scientific research have proved this fact. Even when alcohol is absent smoking can cause
liver ci
hosis and in presence of alcohol smoking increases the rate. Thus to know the
pure effect of alcohol on liver ci
hosis we need to control smoking which implies
smoking is a confounder.
http:
www.hearthealthywomen.org/news-cente
ecent-news/heart-attack-gender-gap-na
ows.html
http:
www.hearthealthywomen.org/news-cente
ecent-news/heart-attack-gender-gap-na
ows.html
ï‚· Interpret the results of the following studies
a. An odds ratio of 1.2 (95% confidence interval: 0.8-1.5) is found for the
association of low socioeconomic status and occu
ence of obesity.
. A relative risk of 3.0 is reported for the association between consumption of
ed meat and the occu
ence of colon cancer. The p-value of the association is
0.15.
c. An odds ratio of 7 (95% confidence interval: 3.0 – 11.4) is found for the
association of smoking and lung cancer.
Ans:
a) An odds ratio of 1.2 (95% confidence interval : 0.8 - 1.5) for the association between
low socioeconomic status and occu
ence of obesity is saying that odds of occurance
of obesity between the...
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