A marginal rank-based inverse normal transformation approach to comparing multiple clinical trial endpoints.

ABSTRACT: The increase in incidence of obesity and chronic diseases and their health care costs have raised the importance of quality diet on the health policy agendas. The healthy eating index is an important measure for diet quality which consists of 12 components derived from ratios of dependent variables with distributions hard to specify, measurement errors and excessive zero observations difficult to model parametrically. Hypothesis testing involving data of such nature poses challenges because the widely used multiple comparison procedures such as Hotelling's T(2) test and Bonferroni correction may suffer from substantial loss of efficiency. We propose a marginal rank-based inverse normal transformation approach to normalizing the marginal distribution of the data before employing a multivari

SUBMITTER: Cai X 

PROVIDER: S-EPMC4938741 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature