Empirical Likelihood Inference for the Rao‐Hartley‐Cochran Sampling Design

The Hartley‐Rao‐Cochran sampling design is an unequal probability sampling design which can be used to select samples from finite populations. We propose to adjust the empirical likelihood approach for the Hartley‐Rao‐Cochran sampling design. The approach proposed intrinsically incorporates sampling weights, auxiliary information and allows for large sampling fractions. It can be used to construct confidence intervals. In a simulation study, we show that the coverage may be better for the empirical likelihood confidence interval than for standard confidence intervals based on variance estimates. The approach proposed is simple to implement and less computer intensive than bootstrap. The confidence interval proposed does not rely on re‐sampling, linearization, variance estimation, design‐effects or joint inclusion probabilities.     

A new confidence interval in errors-in-variables model with known error variance

This paper considers constructing a new confidence interval for the slope parameter in the structural errors-in-variables model with known error variance associated with the regressors. Existing confidence intervals are so severely affected by Gleser–Hwang effect that they are subject to have poor empirical coverage probabilities and unsatisfactory lengths. Moreover, these problems get worse with decreasing reliability ratio which also result in more frequent absence of some existing intervals. To ease these issues, this paper presents a fiducial generalized confidence interval which maintains the correct asymptotic coverage. Simulation results show that this fiducial interval is slightly conservative while often having average length comparable or shorter than the other methods. Finally, we illustrate these confidence intervals with two real data examples, and in the second example some existing intervals do not exist.     

医院青年文化品牌塑造的路径探析

青年是医院的未来,引导青年医务人员树立坚定而充沛的文化自信是激发其积极性、主动性和创造性的重要方式。常州市第一人民医院以涵养文化自信为着力点打造青年文化品牌“青之源”,通过营造学习创新氛围、建设团日活动体系、搭建阅读分享平台、探索涵养青年文化自信的品牌塑造路径等方式,动力、活力、能力三源合流,为青年成长提供正向激励和人文滋养。     

Falsificationism is not just ‘potential’ falsifiability,but requires ‘actual’ falsification: Social psychology,critical rationalism,and progress in science

Based on an analysis of ten popular introductions to social psychology, we will show that Karl Popper's philosophy of ‘critical rationalism’ so far has had little to no traceable influence on the epistemology and practice of social psychology. If Popper is quoted or mentioned in the textbooks at all, the guiding principle of ‘falsificationism’ is reduced to a mere ‘falsifiability’ and some central elements of critical rationalism are left out – those that are incompatible with positivism and inductivism. Echoing earlier attempts to introduce Popper to social psychology by Paul Meehl and Tom Pettigrew, we will argue that a discussing Popper's ideas in more depth could help social psychology to move forward in view of the ‘crisis of confidence’ (Pashler and Wagenmakers, 2012) that has emerged recently in view of the ‘Stapel affair’ and the reports of failures to replicate social psychological experiments in high‐powered replication attempts.     

Identifying as an evidence-based social worker: the influence of attitudes,access, confidence,and education

This study explored United States-based social workers’ (N = 152) attitudes toward, access to, and confidence in engaging in evidence-based practice (EBP), the extent to which social work education prepared them to engage in EBP, and the factors that contributed to their identification as an evidence-based practitioner. Findings indicated that although practitioners had a positive attitude toward engaging in EBP, they were only moderately confident in doing so, rarely accessed evidence, and were only moderately prepared through their education. Believing that EBP should be implemented, more educational preparation, and positive attitudes contributed to greater identification as an evidence-based practitioner, areas that social work and continuing education should further support to enhance social workers’ EBP skills.     

Interval estimation for the breakpoint in segmented regression: a smoothed score‐based approach

This paper is concerned with interval estimation for the breakpoint parameter in segmented regression. We present score‐type confidence intervals derived from the score statistic itself and from the recently proposed gradient statistic. Due to lack of regularity conditions of the score, non‐smoothness and non‐monotonicity, naive application of the score‐based statistics is unfeasible and we propose to exploit the smoothed score obtained via induced smoothing. We compare our proposals with the traditional methods based on the Wald and the likelihood ratio statistics via simulations and an analysis of a real dataset: results show that the smoothed score‐like statistics perform in practice somewhat better than competitors, even when the model is not correctly specified.     

Asymptotic expansions for sequential confidence levels in inverse linear regression

Non-linear renewal theory is used to derive second order asymptotic expansions for the coverage probability of a fixed-width sequential confidence interval for an unknown parameter xin the inverse linear regression model. These expansions are obtained for a two-stage sequential procedure, proposed by Perng and Tong (1974) for the construction of a confidence interval for x.     

Sequential estimation problems for negative exponential populations

The literature on sequential estimation problems for negative exponential populations has been reviewed here, We attempt to bring in all the published and unpublished materials known to us in a fairly coherent fashion. Both the concepts and theoretical findings are discussed.     

Estimation of a process capability index for inverse gaussian distribution

In this article, interval estimates of Clements' process capability index are studied through bootstrapping when the underlying distribution is Inverse Gaussian. The standard bootstrap, the percentile bootstrap, and the bias-corrected percentile bootstrap confidence intervals are compared.