Contingency Table Interpretation

In summary, the data provided shows that there is a relationship between the type of treatment and the response. This is supported by a chi-square test, which indicates that the treatment and response are not independent. Further analysis of the conditional probabilities reveals that there are differences between the probabilities in each cell, suggesting a potential relationship between the two variables. However, it may be difficult to combine categories for a Cochran Armitage Trend Test due to the nature of the treatments.
  • #1
Mogarrr
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Homework Statement


10.24 Is there any relationship between the type of treatment and the response? What form does the relationship take?

Here's that data (column variables are responses):
[itex]
\newcommand\T{\Rule{0pt}{1em}{.3em}}
\begin{array}{|c|c|c|c|c|}
\hline Treatment & +Smear & +Smear,-Culture & -Smear,-Culture & Total\T \\\hline
Peniclillin \T & 40 & 30 & 130 & 200 \\\hline
Spectinomycin(low dose)\T & 10 & 20 & 70 & 100 \\\hline
Spectinomycin(high dose)\T & 15 & 40 & 45 & 100 \\\hline
Total\T & 65 & 90 & 245 & 400 \\\hline
\end{array}
[/itex]

Homework Equations

The Attempt at a Solution


I've already done a chi-square test and found what was hinted in the question, the treatment and response are not independent.

What's a good way to describe the relationship?

I've thought of combining 2 treatment so that I could do Cochran Armitage Trend Test, but given the treatments, I see no clear way of combining categories.

I'm also thinking of commenting on the conditional probabilities and how they differ from the marginal probabilities. (I think the probabilities in the cells can be thought of as conditional probabilities). For example: the probability of a negative smear, negative culture given the treatment was a high dose of spectinomycin is [itex] \frac {45}{100} [/itex] compared to the probability of a negative smear, negative culture, which is [itex] \frac {245}{400} [/itex].
 
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  • #2
Thanks for the post! Sorry you aren't generating responses at the moment. Do you have any further information, come to any new conclusions or is it possible to reword the post?
 

Related to Contingency Table Interpretation

What is a contingency table?

A contingency table is a type of table used in statistics to display the frequency distribution of two or more categorical variables. It shows how the variables are related to each other and can help identify patterns and relationships between them.

How do you interpret a contingency table?

To interpret a contingency table, you first need to look at the row and column totals to see the overall distribution of the variables. Then, you can compare the frequencies within each cell to determine if there is a relationship between the variables. This can be done by calculating the expected frequencies and using statistical tests such as chi-square.

What is the purpose of a contingency table?

The purpose of a contingency table is to visually represent the relationship between two or more categorical variables. It is used to analyze and interpret data in order to identify patterns and associations between the variables.

What is the difference between a contingency table and a frequency table?

A contingency table displays the relationship between two or more categorical variables, while a frequency table only shows the number of occurrences of a single categorical variable. Additionally, contingency tables often include totals and percentages, while frequency tables only include counts.

How can contingency tables be used in data analysis?

Contingency tables can be used in data analysis to explore relationships between categorical variables, to identify patterns and trends, and to test hypotheses. They can also be used to compare the distribution of variables in different groups and to determine the strength of associations between the variables.

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