Two-way Analysis of Variance

Two-way Analysis of Variance

Analysis of variance (ANOVA) is a statistical method that is helpful when one aims to determine variation in the study population. A common type of this analytical technique is the two-way ANOVA. In this form of ANOVA, an individual assesses the interaction between two independent variables that together affect the dependent variable. Essentially, it is a profitable way of controlling extraneous variables that are not the center of focus for the study (Jekel & Katz, 2014). Thus, in public health, a two-way ANOVA affords the best possible option for controlling confounding variables that may affect the validity study findings. In essence, this discussion proposes two examples of public health situations that the two-way ANOVA is applicable.

Firstly and most importantly, one may use the two-way ANOVA to establish the association between poor dietary practices and smoking on the serum cholesterol. The dietary practice and smoking habits are independent variables that have an effect on the dependent variable (blood cholesterol). Determination of the mean differences between the two independent variables will enable one to measure the strength of their influence on the dependent variable (Katz, 2011).

Additionally, testing multiple null hypotheses is another viable example of its use in public health. A case in point is a study that hypothesized parathyroid hormone supplemented in Gonadotropin-releasing hormone can reduce osteoporosis effect due to Gonadotropin-releasing hormone. In this instance, the researchers compared the effect of the treatment alongside other independent variables such as serum calcium on the bone loss (Jekel & Katz, 2014).

Lastly, one can utilize the two-way ANOVA to determine the interaction between the stage of the illness and age of an individual on the effectiveness of a new drug. The age and disease stage are the independent variables while drug effectiveness is the dependent variable. In such a case, both the independent variables have a significant effect on the efficacy of the drug and thus an association between the two is a priority in enhancing the suitability of the drug (Katz, 2011).

In conclusion, indeed a two-way analysis of variance serves a crucial purpose in public health. Thus, health care professionals must understand its applicability if they are to have best returns from it.


















Jekel, J. & Katz, D. (2014). Jekel’s Epidemiology, Biostatistics, Preventive Medicine, and Public Health. W B Saunders Company.

Katz.,. (2011). Multivariable Analysis: A Practical Guide for Clinicians and Public Health Researchers (Cambridge medicine). Cambridge University Press.