Question

What are the pros and cons of using ANOVA testing versus Factorial Designs?

What exactly is the objective of performing Repeated-Measures Designs? Explain in detail.

Answer 1

(a) ANOVA testing versus Factorial Design:

Analysis of Variance (ANOVA) is a statistical test for investigation whether significant difference exists between means of two or more more groups or not. Factorial Designs allow researchers to look at how multiple factors affect a dependent variable, both independently and together.

ANOVA has one independent variable that splits the sample into two or more groups, whereas Factorial Designs have two or more independent variables that split the sample in four or more groups.

Thus, the main advantage of Factorial Designs over ANOVA testing is that by including more than one Independent Variable in a single experiment, the researcher is able to test for the presence of interactions.

(b) In Repeated - Measures Designs, also called Within Subject Designs, measurements are made using only one group of subjects, where tests on each subject are repeated more than once after different treatments.

The objective of performing Repeated - Measures Design:
It is cheaper and easier to conduct an experiment as Repeated - Measures because it is possible to detect statistical differences with a smaller number of subjects. In Repeated - Measures Designs, we re not required to have seperate control group and treatment groups because the same group is both the control and is exposed to all the treatments.