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Suppose a disease can have four different outcomes: Normal, disease_status_1, disease_status_2, and disease_status_3. Let I have two categorical variables in the model: sex (male or female) and age (<15 years, 15-45 years, >45 years).

From different studies, I have collected sample size and effect size of each disease status falling in each category of sex and age variables. For example, number of females who has disease_status_2, effect size of disease_status_2 for female, etc.

To check the association between each category of a variable and various disease outcome, I want to create a table like the following:

\begin{array}{ llll } \hline \text{Variables} & \text{Disease Status 1}& \text{Disease Status 2}& \text{Disease Status 3}\\ \hline Sex &&&\\ \quad Male & -& -& - \\ \quad Female & -& -& - \\ \hline Age&&&\\ \quad <15 & -& -& - \\ \quad 15-45 & -& -& - \\ \quad >45 & -& -& - \\ \hline \hline \end{array}

In place of $-$ in the table, summary effect will be put.

How can I calculate these summary effects to assess these associations? To check these associations, is it sufficient to extract data of sample size and effect size of each disease status falling in each category of sex and age variables?

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