Nonparametric Predictive Inference for diagnostic accuracy

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine and health care. Good methods for determining diagnostic accuracy provide useful guidance on selection of patient treatment, and the ability to compare different diagnostic tests has a direct impact on quality of care. In this paper Nonparametric Predictive Inference (NPI) methods for accuracy of diagnostic tests with continuous test results are presented and discussed. For such tests, Receiver Operating Characteristic (ROC) curves have become popular tools for describing the performance of diagnostic tests. We present the NPI approach to ROC curves, and some important summaries of these curves. As NPI does not aim at inference for an entire population but instead explicitly considers a future observation, this provides an attractive alternative to standard methods. We show how NPI can be used to compare two continuous diagnostic tests.     

Confidence intervals for the regression coefficient in a simple regression model with a balanced two-fold nested error structure

ABSTRACT

In applications using a simple regression model with a balanced two-fold nested error structure, interest focuses on inferences concerning the regression coefficient. This article derives exact and approximate confidence intervals on the regression coefficient in the simple regression model with a balanced two-fold nested error structure. Eleven methods are considered for constructing the confidence intervals on the regression coefficient. Computer simulation is performed to compare the proposed confidence intervals. Recommendations are suggested for selecting an appropriate method.     

Expert system models for inference with imperfect knowledge: A comparative study

This paper presents a detailed comparative study of six major, leading methods for reasoning based on imperfect knowledge: (1) Bayes' rule, (2) Dempster-Shafer theory, (3) fuzzy set theory, (4) Model, (5) Cohen's system of inductive probabilities, and (6) a class of non-monotonic reasoning methods. Each method is presented and discussed in terms of theoretical content, a detailed numerical example, and a list of strengths and limitations. Purposely, the same numerical example is addressed by each method such that we are able to highlight the assumptions, and computational requirements that are specific to each method in a consistent manner.     

Putting the P-Value in its Place

ABSTRACT

As the debate over best statistical practices continues in academic journals, conferences, and the blogosphere, working researchers (e.g., psychologists) need to figure out how much time and effort to invest in attending to experts' arguments, how to design their next project, and how to craft a sustainable long-term strategy for data analysis and inference. The present special issue of The American Statistician promises help. In this article, we offer a modest proposal for a continued and informed use of the conventional p-value without the pitfalls of statistical rituals. Other statistical indices should complement reporting, and extra-statistical (e.g., theoretical) judgments ought to be made with care and clarity.     

Assessing the Statistical Analyses Used in Basic and Applied Social Psychology After Their p-Value Ban

ABSTRACT

In this article, we assess the 31 articles published in Basic and Applied Social Psychology (BASP) in 2016, which is one full year after the BASP editors banned the use of inferential statistics. We discuss how the authors collected their data, how they reported and summarized their data, and how they used their data to reach conclusions. We found multiple instances of authors overstating conclusions beyond what the data would support if statistical significance had been considered. Readers would be largely unable to recognize this because the necessary information to do so was not readily available.     

Inference for Mixtures

In this article, we consider the problem of estimating certain “parameters” in a mixture of probability measures. We show that a single sample is typically suitable for estimating the component measures, but not suitable for estimating the mixing measures, especially when consistency is required. To have consistent estimators of the mixing measure, several samples with increasing size are needed in general.     

俞敏先生训诂方法研究

俞敏先生将传统训诂方法和现代语言学理论方法融会贯通,形成了他独特的研究方法,从而为汉语古文献的研究提出了很多独到的见解。他的训诂研究方法可以归结为3个方面:将因声求义与因形求义相结合进行训诂研究;首次利用语流音变对古文献进行研究;率先运用汉藏比较进行训诂研究。     

贝叶斯推理主观性探析——对无差别原则和不变性的考察

作为当代发展最为迅猛的一种科学研究方法——贝叶斯主义方法,尽管已经深入到了科学研究的方方面面,但其先天的“先验”、“主观性”等标签使其陷入了不必要的纷争之中.通过贝叶斯对无差别原则和不变性原理的考察,发现先验概率的无约束即主观性,是贝叶斯主义的一个优点,更重要的是该主观性的产生是由严格的“推理机”——归纳逻辑所定义出的.     

Least squares and generalized least squares in models with orthogonal block structure

Besides the basic model, Kronecker products of rotated models are used to isolate the variance components as parameters of a linear model. A characterization of BLUE given by Zmy?lony (1980) is applied to the different models. Generalized least squares are used to complete the estimation.     

收入基尼系数的统计推断

 基尼系数估计量的统计推断是基尼系数研究的一个重点。本文我们使用Davidson（2009）提出的近似大样本渐进分布方法,对收入基尼系数估计量进行统计推断,包括计算估计量的标准差、构造置信区间和进行假设检验。通过模拟试验,我们验证了在小样本情形下,依据该方法所做的统计推断具有较高的可靠性。在此基础上,我们对我国城镇居民的真实收入基尼系数进行了统计推断。