Statistical methods for longitudinal and censored or missing data

在自然资源管理方面，越来越多的决策基于对复杂数据库的分析。这种复杂性可能来自数据库的地理和/或空间性质（例如，佩戴GPS设备的动物每天访问的几个地点的信息）或其纵向性质（例如，现在常见的做法是在同一实验单元上进行多次测量，无论是动物、鱼群还是气象站）。

In the management of natural resources, decisions are becoming increasingly based on the analysis of complex databases. This complexity may arise from the geographic and/or spatial nature of the database (e.g., information on several daily locations visited by animals wearing GPS devices) or from its longitudinal nature (e.g., it is now common practice to take multiple measurements on a same experimental unit, be it an animal, a fish population, a weather station). A difficulty that is common to many such situations is the fact that some pieces of information are missing or incomplete in the database and/or elements of the models are not directly observed in the data. For instance when measuring the growth of trees, if a tree is dead at the time of the last measurement but was alive at the second to last measurement, then the exact time of death of this tree is not known exactly, but only to lie in the time interval defined by the last two measurements; such incomplete information is known as "interval censoring". Or when modeling how bison select their habitat, the "tastes" of each animal are explicitly included as elements of the statistical model, but no direct measurements of these "tastes" are part of the database. The main objective of this research program is to develop and improve models and methods for the analysis of longitudinal data when some observations are censored, missing or unobserved, with a particular focus on the methods used in the management of natural resources. Using statistical methods to handle missing data, we will propose new models and methods for the joint modeling of longitudinal and survival data (e.g., tree growth modeling), for the modeling of longitudinal data using latent state space processes (e.g., commercial fish stock modeling) and for the estimation of resource selection functions (e.g., animal habitat selection studies).