Multivariate Analysis of Variance in Research
Multivariate analysis is one of the most applicable methods of variance analysis in the world. The method is appropriate for use when there are two or more variables that need to be analyzed at one particular instance. This is done to get a clear understanding of the relationship that exists between these variables hence coming up with valid results and conclusions for the study. An example of a scenario where multivariate analysis may be used by a researcher is when he or she needs to find the relationship between an independent and a dependent variable. To do this, the researcher introduces an external variable to make sure that the correlation between the dependent and the independent variables is not invalid.
Several research questions in the social sciences are answered with the help of statistical models such as multiple linear regression analysis, ANOVA, and MANOVA. Multivariate analysis is, therefore, an important tool in handling issues in social studies. This type of analysis is a capability-based design. In addition, the method can also be used as an inverse design. This way, each variable may be looked at as an independent variable. Therefore, the multivariate analysis may be appropriate to be used in the analysis of alternatives of a research study to fulfill the needs and requirements of the research questions and hypotheses. It may also be used to analyze concepts in changing situations.
I was personally interested in factorial analysis which is a statistical tool that may be used to analyze relationships among a large number of variables. For one to use factorial analysis, it is required that one has data in the form of correlations. This means that all the assumptions that underlie correlations apply. In factorial analysis, there are two main types of analyses which include principal component analysis and common factor analysis. This method would be important for my studies as it provides unique solutions and allows for the reconstruction of the initial data from the results.