We propose a new classification method for longitudinal data based on a semiparametric approach. Our approach builds a classifier by taking advantage of modeling information between response and covariates for each class ...
This dissertation is about the likelihood analysis of ordered categorical responses in a longitudinal/spatial study, meaning regression-like analysis when the response variable is categorical with ordered categories, and ...
The process of silvicultural thinning has become very controversial recently with
regards to fire protection and management for old-growth conditions and biodiversity. Therefore, an unthinned control stand and 3 differe ...
This thesis consists of three papers which investigate marginal models,
nonparametric approaches, generalized mixed effects models and variance
components estimation in longitudinal data analysis.
In the first paper, ...
In cross-cultural studies, respondents from specific cultures may have
different product preferences and scale usage. Combining data from different
cultures will result in departures from the basic assumptions of analy ...
Missing data can lead to biased and inefficient estimation if the missing mechanism is not
taken into account in the analysis. In this dissertation we propose two estimators that,
under fairly general conditions, are a ...
The varying-coefficient model is flexible and powerful for modeling the dynamic changes of regression
coefficients. It is important to identify significant covariates associated with response
variables, especially for ...