Statistical methods of handling ordinal longitudinal responses with incomplete observations
Format: CPS Abstract
The rate of survival of human immunodeficiency virus (HIV) positive individuals resume to ameliorate with the consumption of highly antiretroviral therapy (HAART), but pulmonary disease prevalence has been growing unabated among them. The data was characterized by intermittent missing data due to the patient's failure to disclose vital health information and absence on visit days. Handling missing data was a difficult challenge in the dataset. We analyzed the data under the missing at-random missingness assumption. We compared the effects of marginal and conditional models in the study. Amongst the methods, the ordinal negative binomial model without any form of imputation performs greatly in simulation studies and real applications than multiple imputation-based generalized estimating equations (MI-GEE) and other models used.