Multilevel Correlated Data:
Hierarchical data, longitudinal data, repeated measures, mixed effects, overdispersion

Multilevel data are very common in sociological, behavioral and biomedical researches. The data could come from longitudinal community surveys, genetic family studies or spatial-temporal studies, which could be used to investigate and analyze some health outcomes, e.g. some treatment intervention. Such data could be very complex when it consists of multiple levels of data structures. The data might have factors such as the community, family, patient and repeated measures over time nested or crossed in each other. The difficulties in the analysis of correlated data involve within-subject correlation, between-subject variations, heterogeneities and high-dimensional hierarchical structures, etc. When the outcome is binary, the analysis becomes very challenging. In a longitudinal study on customer’s satisfaction rate among stores in a franchise business, the data could be multivariate multinomial/binomial with hierarchical structures. Efficient methods and computational algorithms have been developed, and the software Multicorr is available for use.

Integrated Development Environment for Analysis:
Data analysis, GUI designer, R, Web application

Many new and advanced analytic methods and software are developed every day. Innovative methods can help us understand the nature of the underlying problems in data and have a better chance to solve challenges in data analysis. The problem is whether or not the software of such innovative methods has a friendly graphical user interface (GUI) to reach a browser audience with limited programming training. This is one of the challenges in software usability. An integrated development environment (IDE) for analysis will assist module developers in developing advanced methods with calculating engines such as R, Java and C++. To add the strength of a module, tools could also be used for composing dynamic graphics and outputs with multi-media formats.

Longit Informatics Center for Longitudinal Studies:
Longitudinal data analysis, dynamic graphics, solution exhibitor, web publication, customization

This is a customizable virtual informatics center for sharing data, running data analysis, visualizing results, publishing reports and finding solutions related to longitudinal studies. This informatics center contains a data center, analytic methods, software modules, dynamic graphical environments, data analysis solutions, web publications and solution exhibitors.

StatGL (Statistical Graphical Library):
Statistical graphical methods, dynamic graphics, dynamic linkage

This StatGL consists of fundamental statistical graphical methods and interactive graphical tools. Graphical methods such as the histogram plot, density plot and xy-plot are useful in exploratory data analysis. Some of these graphics can be dynamically linked together. Their graphical parameters can be set up in a set of control panels. Using animation parameters, dynamic graphics and animation can be constructed.