In the presence of covariate measurement error, there has been extensive interest in developing estimation methods for parameters associated with various survival ...

We introduce novel regression extrapolation based methods to correct the often large bias in subsampling variance estimation as well as hypothesis testing for spatial point and marked point processes.

Introduces exploratory data analysis, probability theory, statistical inference, and data modeling. Topics include discrete and continuous probability distributions, expectation, laws of large numbers ...

Description: Introductory statistical methods, with emphasis on applications in biology. Topics include descriptive statistics, binomial and normal distributions, confidence interval estimation, ...

The course provides a precise and accurate treatment of statistical ideas, methods and techniques. Topics covered are sampling distributions of statistics, point estimation, interval estimation, ...

Generally, the use of ordinary missing data estimation, the UNTIE transformation, and the UNTIE= a-option should be avoided, particularly with hypothesis tests. With these options, parameters are ...

The purpose of this paper is to examine whether the efficiency structure hypothesis holds true for major Japanese commercial banks. The efficiency structure hypothesis, developed by Demesetz (1973), ...

This course presents fundamental principles of statistics in the context of business-related data analysis and decision making, including methods of summarizing and analyzing data, statistical ...