Biostatistics, help deciding on a test

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SUMMARY

The forum discussion centers on determining the appropriate statistical test to assess the relationship between receiving an antibiotic and receiving an antibiotic culture in a hospital setting. Participants suggest using either McNemar's Test or the Chi-Square Test for Independence, with a preference for McNemar's Test due to the dependent nature of the samples. However, given the small sample size, Fisher's Exact Test is recommended as a more accurate alternative. The conversation highlights the nuances of hypothesis testing in biostatistics, particularly in relation to dependent samples.

PREREQUISITES
  • Understanding of McNemar's Test for paired nominal data
  • Knowledge of Chi-Square Test for Independence
  • Familiarity with Fisher's Exact Test for small sample sizes
  • Basic concepts of dependent and independent samples in statistics
NEXT STEPS
  • Research the application of McNemar's Test in biostatistics
  • Learn about the Chi-Square Test for Independence and its assumptions
  • Explore Fisher's Exact Test and its implementation in small sample scenarios
  • Study the differences between within-subject and between-subject designs in statistical analysis
USEFUL FOR

Biostatisticians, healthcare researchers, and students studying statistics who need to understand the application of statistical tests for analyzing relationships in dependent samples.

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Homework Statement


Refer to Table 2.11.
10.6 What significance test can be used to assess whether there is a relationship between receiving an antibiotic and receiving an antibiotic culture while in the hospital?

Here's my attempt of recreating the table:
\newcommand\T{\Rule{0pt}{1em}{.3em}}<br /> \begin{array}{|c|c|c|}<br /> \hline ID &amp; Antibiotic(1=Yes,2=NO) &amp; Culture(1=Yes,2=NO) \T \\\hline<br /> 1 \T &amp; 2 &amp; 2 \\\hline<br /> 2 \T &amp; 2 &amp; 1 \\\hline<br /> 3 \T &amp; 2 &amp; 2 \\\hline<br /> 4 \T &amp; 2 &amp; 2 \\\hline<br /> 5 \T &amp; 2 &amp; 2 \\\hline<br /> 6 \T &amp; 1 &amp; 2 \\\hline<br /> 7 \T &amp; 1 &amp; 1 \\\hline<br /> 8 \T &amp; 2 &amp; 2 \\\hline<br /> 9 \T &amp; 2 &amp; 2 \\\hline<br /> 10 \T &amp; 2 &amp; 1 \\\hline<br /> 11 \T &amp; 2 &amp; 1 \\\hline<br /> 12 \T &amp; 2 &amp; 2 \\\hline<br /> 13 \T &amp; 1 &amp; 2 \\\hline<br /> 14 \T &amp; 1 &amp; 1 \\\hline<br /> 15 \T &amp; 2 &amp; 1 \\\hline<br /> 16 \T &amp; 2 &amp; 2 \\\hline<br /> 17 \T &amp; 1 &amp; 2 \\\hline<br /> 18 \T &amp; 2 &amp; 2 \\\hline<br /> 19 \T &amp; 1 &amp; 2 \\\hline<br /> 20 \T &amp; 2 &amp; 2 \\\hline<br /> 21 \T &amp; 2 &amp; 2 \\\hline<br /> 22 \T &amp; 1 &amp; 2 \\\hline<br /> 23 \T &amp; 2 &amp; 2 \\\hline<br /> 24 \T &amp; 2 &amp; 2 \\\hline<br /> 25 \T &amp; 2 &amp; 2 \\\hline<br /> \end{array}<br />

Homework Equations



Two tests from this chapter are McNemar's Test and a Chi-Square Test for Independence

The Attempt at a Solution



I have no idea which test to use. Since the problem is asking for a test for association, I would think a chi-square test is appropriate, however the nature of the data makes me question that. I would think that, since we are looking at the same subject in the table, this is a dependent sample. However, the null hypothesis for McNemar's test is that the marginal probabilities are equal or that the probability of each type of discordant pair are equal. The problem isn't asking that, just asking if there is a relationship?

Any help would be greatly appreciated.
 
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I would tend to agree with the Chi squared test.
You are testing for dependence.
 
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Mogarrr said:

Homework Statement


Refer to Table 2.11.
10.6 What significance test can be used to assess whether there is a relationship between receiving an antibiotic and receiving an antibiotic culture while in the hospital?

Here's my attempt of recreating the table:
\newcommand\T{\Rule{0pt}{1em}{.3em}}<br /> \begin{array}{|c|c|c|}<br /> \hline ID &amp; Antibiotic(1=Yes,2=NO) &amp; Culture(1=Yes,2=NO) \T \\\hline<br /> 1 \T &amp; 2 &amp; 2 \\\hline<br /> 2 \T &amp; 2 &amp; 1 \\\hline<br /> 3 \T &amp; 2 &amp; 2 \\\hline<br /> 4 \T &amp; 2 &amp; 2 \\\hline<br /> 5 \T &amp; 2 &amp; 2 \\\hline<br /> 6 \T &amp; 1 &amp; 2 \\\hline<br /> 7 \T &amp; 1 &amp; 1 \\\hline<br /> 8 \T &amp; 2 &amp; 2 \\\hline<br /> 9 \T &amp; 2 &amp; 2 \\\hline<br /> 10 \T &amp; 2 &amp; 1 \\\hline<br /> 11 \T &amp; 2 &amp; 1 \\\hline<br /> 12 \T &amp; 2 &amp; 2 \\\hline<br /> 13 \T &amp; 1 &amp; 2 \\\hline<br /> 14 \T &amp; 1 &amp; 1 \\\hline<br /> 15 \T &amp; 2 &amp; 1 \\\hline<br /> 16 \T &amp; 2 &amp; 2 \\\hline<br /> 17 \T &amp; 1 &amp; 2 \\\hline<br /> 18 \T &amp; 2 &amp; 2 \\\hline<br /> 19 \T &amp; 1 &amp; 2 \\\hline<br /> 20 \T &amp; 2 &amp; 2 \\\hline<br /> 21 \T &amp; 2 &amp; 2 \\\hline<br /> 22 \T &amp; 1 &amp; 2 \\\hline<br /> 23 \T &amp; 2 &amp; 2 \\\hline<br /> 24 \T &amp; 2 &amp; 2 \\\hline<br /> 25 \T &amp; 2 &amp; 2 \\\hline<br /> \end{array}<br />

Homework Equations



Two tests from this chapter are McNemar's Test and a Chi-Square Test for Independence

The Attempt at a Solution



I have no idea which test to use. Since the problem is asking for a test for association, I would think a chi-square test is appropriate, however the nature of the data makes me question that. I would think that, since we are looking at the same subject in the table, this is a dependent sample. However, the null hypothesis for McNemar's test is that the marginal probabilities are equal or that the probability of each type of discordant pair are equal. The problem isn't asking that, just asking if there is a relationship?

Any help would be greatly appreciated.

You could use either a NcNemar or a chi-squared test, but since the sample size is small, those will be inaccurate. If you can, you should try Fisher's exact test. See, eg., http://yatani.jp/teaching/doku.php?id=hcistats:chisquare .
 
Last edited:
I have an exact test for small samples, however I wanted to talk about one more thing concerning this problem. I just learned that McNemar's test can be viewed as a within Chi-Squared Test.

Do you think this data is an example of a within-subject design?
 

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