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Part B, C, and D: Part B Use STATA where relevant. Interpret all of your results. You cannot use the same articles as your classmates nor can you use the same article for both 1 and 2-they must be TWO...

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Part B, C, and D:

Part B

Use STATA where relevant. Interpret all of your results. You cannot use the same articles as your classmates nor can you use the same article for both 1 and 2-they must be TWO DIFFERENT ARTICLES.


1. Find a journal article that uses a chi-squared test (Pearson’s test) to test for

independence of two categorical variables (in a contingency table).

  1. Write the reference to the article(hint:can use pubmed.gov or a particular medical journal and search for “chi-squared test” and a specific disease or

    public health area that interests you),

  2. State the appropriate hypotheses to test for independence of content of interest.

  3. copy the contingency table into your homework,

  4. Complete and reproduce the hypothesis test and their p-value (show the STATAoutput and do by hand expressing formulas appropriately).

  5. What conclusion did the investigators draw Did they use the correct statistical test?If not, did they come to the right conclusion?

2. Find a journal article that uses a Fisher’s exact test to test for independence of two categorical variables (in a contingency table).

  1. Write the reference to the article (hint:can use pubmed.gov or a particular medical journal and search for “chi-squared test” and a specific disease or public health area that interests you),

  2. State the appropriate hypotheses to test for independence of content of interest.

  3. Why did they use this test instead of the chi-squared test?

  4. copy the contingency table into your homework, and

  5. Complete and reproduce the hypothesis test and their p-value (show the STATAoutput and do by hand expressing formulas appropriately).

  6. What conclusion did the investigators draw? Did they use the correct statistical test?If not, did they come to the right conclusion?

Part C

Use the Weight dataset.
First create three body mass index (BMI) groups: 30. Note that you will have to convert the data to the correct units.

1) Test the hypothesis that there is an overall mean difference in systolic blood pressure (sbp) levels among the three different BMI groups.

  1. Write down the null and alternative hypotheses using appropriate notation

  2. Check the assumptions of your test. Try with and withouttransformations on the data.

  3. Conduct the test (i) with and (ii) without transformations on the data.

  4. Perform pair wise comparisons of the means using a multiple comparison adjustment (i) with and (ii) without transformations on the data.

  5. Interpret your results with and without transformations of the data and decide which is most appropriate.

Part D

Download Smoke data and complete the following questions in Stata.

1.Why are nonparametric methods well suited to study whether there is a difference between numbers of days abstinent from smoking for males vs females? Answer your question by checking the assumptions for normality, performing appropriate transformations and again checking for the normality.

2. Use the appropriate nonparametric method to test whether there is a difference between numbers of days abstinent from smoking for males vs females?

3. Suppose that there was a subset of individual smokers who had undergone treatment with the eventual goal to quit smoking completely by 6 months follow-up. Suppose we had information on the number of days abstained from the last cigarette at baseline and at a 2- month interim. How would you test whether the increase in days abstained from the last cigarette differed among males and females considering what you know about this dataset?

Answered Same Day Aug 02, 2021

Solution

Bolla V V Satyanarayana answered on Aug 03 2021
125 Votes
B)
1. Using Table-2 in this article (https:
www.ncbi.nlm.nih.gov/pmc/articles/PMC6299263/)
C)
Contingency Table:
    Sex
    Health Care Unitization Pattern
    Total
    
    Health visit, No Dental visit
    No Health visit, Dental visit
    Both Health visit and Dental visit
    No Health visit or Dental visit
    
    Male
    1794
    302
    2247
    714
    5057
    Female
    1919
    167
    2964
    338
    5388
    Total
    3713
    469
    5211
    1052
    10445
2. Using Table 3
Comparison of Probing Depth (PD) component of Community Periodontal Index between non-obese and obese groups(https:
www.ncbi.nlm.nih.gov/pmc/articles/PMC6905353/)
c)
Chi square Test’s Assumption was not satisfied for this data
Assumptions of Chi square test
Chi Square test should not apply when the any cell frequency value less than 5 or equal to 5
Chi square test should not apply when the total frequency less than 50(Small sample sizes)
But Fisher -Exact test Should apply for Sample size. So we use Fisher’s Exact test instead of Chi square test.
d)
Contingency Table:
    PD
    Group
    Total
    
    None OBSE
    OBSE
    
    1 COUNT
    4
    0
    4
    2 COUNT
    20
    11
    31
    3 COUNT
    18
    22
    40
    4 COUNT
    0
    9
    9
    Total
    42
    42
    84
C)
First, we convert the Height and Weight into BMI
We take three groups that Group 1: Body mass index for 50, Group2: Body Mass index for 51, Group 3: Body mass index for 52
We want to test the hypothesis that there is a significance difference between Mean Systolic blood pressure among three different Body Mass index groups(50,51 and 52)
From the output
Test statistic value of F =1.14
P-value = 0.752
From the output of Bonfe
oni comparisons test:
There is no significance different between mean pair of Systolic Blood pressure of Body mass index Group 50 and Body mass index Group 51 (P-value = 0.395 > 0.05)
There is no significance different between mean pair of Systolic Blood pressure of Body mass index Group 51 and Body mass index Group 52 (P-value = 1.000 > 0.05)
There is no significance different...
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