An investigator finds out that 5 independent factors influence the occurrence of a disease. Comparison of multiple factors that are responsible for the disease can be assessed by:
**Core Concept**
The concept of analyzing multiple factors influencing a disease is crucial in epidemiology and research. The investigator is looking to understand the relationship between multiple independent variables and a dependent variable (the disease).
**Why the Correct Answer is Right**
To assess the relationship between multiple independent factors and a dependent variable, the investigator should use **Multiple Linear Regression (MLR)**. MLR is a statistical method that allows the researcher to model the relationship between a dependent variable and one or more independent variables while controlling for the effects of other independent variables. This is particularly useful when there are multiple factors influencing the disease, as it enables the researcher to determine the unique contribution of each factor to the disease.
**Why Each Wrong Option is Incorrect**
* **Option A:** **Chi-Square Test** is a statistical method used to determine the significance of the difference between expected and observed frequencies in a categorical variable. It is not suitable for analyzing multiple independent factors influencing a disease.
* **Option B:** **Analysis of Variance (ANOVA)** is a statistical method used to compare the means of three or more groups. While ANOVA can be used to analyze the effect of multiple factors on a disease, it assumes independence of observations and does not account for the relationships between the independent variables.
* **Option D:** **Survival Analysis** is a statistical method used to analyze the time-to-event data. It is not suitable for analyzing multiple independent factors influencing a disease.
**Clinical Pearl / High-Yield Fact**
When analyzing multiple factors influencing a disease, it is essential to use a statistical method that can account for the relationships between the independent variables. Failure to do so can lead to biased estimates and incorrect conclusions.
**Correct Answer:** C. Multiple Linear Regression.