Xiaochun Li – författare

Multivariate analysis is a mainstay of statistical tools in the analysis of biomedical data. It concerns with associating data matrices of n rows by p columns, with rows representing samples (or patients) and columns attributes of samples, to some response variables, e.g., patients outcome. Classically, the sample size n is much larger than p, the number of variables. The properties of statistical models have been mostly discussed under the assumption of fixed p and infinite n. The advance of biological sciences and technologies has revolutionized the process of investigations of cancer. The biomedical data collection has become more automatic and more extensive. We are in the era of p as a large fraction of n, and even much larger than n. Take proteomics as an example. Although proteomic techniques have been researched and developed for many decades to identify proteins or peptides uniquely associated with a given disease state, until recently this has been mostly a laborious process, carried out one protein at a time. The advent of high throughput proteome-wide technologies such as liquid chromatography-tandem mass spectroscopy make it possible to generate proteomic signatures that facilitate rapid development of new strategies for proteomics-based detection of disease. This poses new challenges and calls for scalable solutions to the analysis of such high dimensional data. In this volume, we will present the systematic and analytical approaches and strategies from both biostatistics and bioinformatics to the analysis of correlated and high-dimensional data.

This is the first book that uses the Harris – Todaro (H-T) model to study contemporary economic issues in developing countries, with a particular focus on China. The zenith of research utilizing this model occurred in the 1990s, primarily addressing the impact of economic policies during labor migration on wages and employment across various sectors, international trade, urban unemployment rates, and social welfare. After nearly four decades, research in this area gradually faded from the spotlight. Post-2010, however, there has been a resurgence in H-T model studies. Scholars have begun using this model to explore contemporary issues, revealing unprecedented insights and showcasing its robust applicability and vitality.

The book features 13 papers authored by contributors since 2018, each utilizing the H-T model and published in various academic journals. It delves into pivotal issues of contemporary economic development in developing countries like China, including dual agricultural economy, producer services, foreign direct investment, agricultural pollution, migrant workers’ remittances, and agricultural human capital investment. The book constructs general equilibrium models by integrating these topics with the H-T model, providing a framework to assess the impact of economic policies. Methodologically, it goes beyond conventional approaches by introducing constant elasticity of substitution functions and other methods to precisely express contemporary economic problems. Numerical simulations to examine the impact of economic policies are also used. Beyond presenting solutions to the current economic problems in developing countries, this book provides academic references for economic theory researchers.