Non-rejective implementations of the Sampford sampling design

Sampford sampling is a method for unequal probability sampling. There exist several implementations of the Sampford sampling design which all are rejective methods, i.e. the sample is not always accepted. Thus the existing methods can be time consuming or even infeasible in some situations. In this paper, a fast and non-rejective list-sequential method, which works in all situations, is presented. The method is a modification of a previously existing rejective list-sequential method. Another list-sequential implementation of Sampford sampling is also presented.     

Modelling and simulation for one‐day cricket

This article is concerned with the simulation of one‐day cricket matches. Given that only a finite number of outcomes can occur on each ball that is bowled, a discrete generator on a finite set is developed where the outcome probabilities are estimated from historical data involving one‐day international cricket matches. The probabilities depend on the batsman, the bowler, the number of wickets lost, the number of balls bowled and the innings. The proposed simulator appears to do a reasonable job at producing realistic results. The simulator allows investigators to address complex questions involving one‐day cricket matches. The Canadian Journal of Statistics © 2009 Statistical Society of Canada     

Inference after variable selection using restricted permutation methods

When confronted with multiple covariates and a response variable, analysts sometimes apply a variable‐selection algorithm to the covariate‐response data to identify a subset of covariates potentially associated with the response, and then wish to make inferences about parameters in a model for the marginal association between the selected covariates and the response. If an independent data set were available, the parameters of interest could be estimated by using standard inference methods to fit the postulated marginal model to the independent data set. However, when applied to the same data set used by the variable selector, standard (“naive”) methods can lead to distorted inferences. The authors develop testing and interval estimation methods for parameters reflecting the marginal association between the selected covariates and response variable, based on the same data set used for variable selection. They provide theoretical justification for the proposed methods, present results to guide their implementation, and use simulations to assess and compare their performance to a sample‐splitting approach. The methods are illustrated with data from a recent AIDS study. The Canadian Journal of Statistics 37: 625–644; 2009 © 2009 Statistical Society of Canada     

汉布林论评估论证的三种标准

论证评估是论证逻辑的核心，评估标准的确立是论证评估得以展开的基础。在《谬误》中，汉布林分析、评述了论证评估的真值的、认识的和辩证的标准，三种标准彼此相互兼容、互相补充，体现了论证的实践的和语用的维度。     

Estimating functions in the Bayesian paradigm

Received: August 3, 1998; revised version: June 9, 1999     

The expected length of male retirement in the United States, 1850–1990

This paper estimates the expected length of retirement for each labor market cohort between 1850 and 1990. Since 1850, the expected length of retirement has increased by more than six-fold and now represents up to 30% of male length of life after entry into the labor force. The rise of the duration of retirement during the twentieth century is analyzed according to the effects of mortality decline and of decreased age of retirement. Implications of the result for a number of economic issues, including the relative importance of life-cycle savings and the potential saving effect of Social Security, are discussed. Received: 22 September 1999/Accepted: 11 July 2000     

Pseudo MLE for semiparametric transformation model with doubly truncated data

In this article, we consider the efficient estimation of the semiparametric transformation model with doubly truncated data. We propose a two-step approach for obtaining the pseudo maximum likelihood estimators (PMLE) of regression parameters. In the first step, the truncation time distribution is estimated by the nonparametric maximum likelihood estimator (Shen, 2010a) when the distribution function $K$ of the truncation time is unspecified or by the conditional maximum likelihood estimator (Bilker and Wang, 1996) when $K$ is parameterized. In the second step, using the pseudo complete-data likelihood function with the estimated distribution of truncation time, we propose expectation–maximization algorithms for obtaining the PMLE. We establish the consistency of the PMLE. The simulation study indicates that the PMLE performs well in finite samples. The proposed method is illustrated using an AIDS data set.     

Efficacy of newer medications for lower urinary tract symptoms attributed to benign prostatic hyperplasia: a systematic review

We conducted a systematic review to evaluate the efficacy and adverse effects of newer drugs used to treat lower urinary tract symptoms (LUTS). The drugs were either Food and Drug Administration (FDA) approved for benign prostatic hyperplasia (BPH) or not FDA approved for BPH but have been evaluated for treatment of BPH since 2008. We searched bibliographic databases through September 2017. We included randomized controlled trials (RCTs) lasting one month or longer published in English. Outcomes of interest were LUTS assessed by validated measures. Efficacy was interpreted using established thresholds indicating clinical significance that identified the minimal detectable difference. Twenty-three unique, generally short-term, RCTs evaluating over 9000 participants were identified. Alpha-blocker silodosin and phosphodiesterase type 5 inhibitor tadalafil were more effective than placebo in improving LUTS (moderate strength evidence) but these drugs had more adverse effects, including abnormal ejaculation (silodosin). Anticholinergics were only effective versus placebo when combined with an alpha-blocker. Evidence was generally low strength or insufficient for other drugs. Evidence was insufficient to assess long-term efficacy, prevention of symptom progression, need for surgical intervention, or long-term adverse effects. Longer trials are needed to assess the effect of these therapies on response rates using established minimal detectable difference thresholds, disease progression, and harms.     

Asymptotic normality and mean consistency for the weighted estimator in nonparametric regression models

In this paper, we mainly study the asymptotic properties of weighted estimator for the nonparametric regression model based on linearly negative quadrant dependent (LNQD, for short) errors. We obtain the rate of uniformly asymptotic normality of the weighted estimator which is nearly $O\left(n^{?1∕4}\right)$ when the moment condition is appropriate. The results generalize the corresponding ones of Yang (2003) from NA samples to LNQD samples and improve or extend the corresponding one of Li et al. (2012) for LNQD samples. Moreover, we obtain some results on mean consistency, uniformly mean consistency, and the rate of mean consistency for the weighted estimator. Finally we carry out some simulations to verify the validity of our results.     

Class Size and Educational Policy: Who Benefits from Smaller Classes?

ABSTRACT

The impact of class size on student achievement remains an open question despite hundreds of empirical studies and the perception among parents, teachers, and policymakers that larger classes are a significant detriment to student development. This study sheds new light on this ambiguity by utilizing nonparametric tests for stochastic dominance to analyze unconditional and conditional test score distributions across students facing different class sizes. Analyzing the conditional distributions of test scores (purged of observables using class-size specific returns), we find that there is little causal effect of marginal reductions in class size on test scores within the range of 20 or more students. However, reductions in class size from above 20 students to below 20 students, as well as marginal reductions in classes with fewer than 20 students, increase test scores for students below the median, but decrease test scores above the median. This nonuniform impact of class size suggests that compensatory school policies, whereby lower-performing students are placed in smaller classes and higher-performing students are placed in larger classes, improves the academic achievement of not just the lower-performing students but also the higher-performing students.