MANOVA is used to compare multivariate sample means across more than two dependent variables, commonly applied in education and psychology research. However, some papers incorrectly use MANOVA for univariate research questions rather than multivariate questions. Additionally, some MANOVA assumptions like linearity of dependent variables and homogeneity of covariance matrices can be difficult to satisfy. More modern alternatives like linear mixed effects models and multiple imputation may be superior for analyzing repeated measurements or missing data. The document discusses challenges with MANOVA and potential alternative statistical methods that are better suited for certain research questions and designs.