The often overlooked issue of statistical power: This and other issues regarding assessing importance weighting in quality of life measures

In the area of quality of life research, researchers may ask respondents to rate importance as well as satisfaction of various life domains (such as job and health) and use importance ratings as weights to calculate overall, or global, life satisfaction. The practice of giving more important domains more weight, known as importance weighting, has not been without controversy. Several previous studies assessed importance weighting using the analytical approach of moderated regression. This study discusses major issues related to how importance weighting has been assessed. Specifically, this study highlights that studies on importance weighting without considering statistical power are prone to type II error, i.e., failing to reject the null hypothesis of no significant weighting effect when the null hypothesis is actually false. The sample size required for adequate statistical power to detect importance weighting functions appeared larger than most previous studies could offer.     

PATTERN RECOGNITION VIA ROBUST SMOOTHING WITH APPLICATION TO LASER DATA

Nowadays airborne laser scanning is used in many territorial studies, providing point data which may contain strong discontinuities. Motivated by the need to interpolate such data and preserve their edges, this paper considers robust nonparametric smoothers. These estimators, when implemented with bounded loss functions, have suitable jump‐preserving properties. Iterative algorithms are developed here, and are equivalent to nonlinear M‐smoothers, but have the advantage of resembling the linear Kernel regression. The selection of their coefficients is carried out by combining cross‐validation and robust‐tuning techniques. Two real case studies and a simulation experiment confirm the validity of the method; in particular, the performance in building recognition is excellent.     

Interfamily economic exchange: A function of culture or economics?

This study explores differences in inter-household exchange of goods and services in Anglo- and Mexican-American families controlling for income level and for ethnicity. The extent of such exchange, its perceived importance to the family's quality of life, satisfaction with the exchange, and the relation of persons in the exchange process are examined. Significant differences are found more often between higher income Anglo- and Mexican-Americans than between low-income families, both in the family providing goods and services for others and in the receipt of them. Higher income Mexican-American families are more likely than their Anglo- counterparts to exchange with relatives. Ethnic effects are more prevalent in higher income households than in low-income households. Economic effects are more predominant than ethnic effects.This study contributes to interregional Agricultural Experiment Station Research Project NC-128, Quality of Life as Influenced by Area of Residence. Cooperating states: Arizona, California, Colorado, Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, Nevada, Ohio, Texas.Flora L. Williams' current research interests include income adequacy, financial problems, and indicators of change in economic well-being. She is an Associate Professor, Consumer Sciences and Retailing, Purdue University, West Lafayette, IN 47907.     

To be or not to be valid in testing the significance of the slope in simple quantitative linear models with autocorrelated errors

In this article, the validity of procedures for testing the significance of the slope in quantitative linear models with one explanatory variable and first-order autoregressive [AR(1)] errors is analyzed in a Monte Carlo study conducted in the time domain. Two cases are considered for the regressor: fixed and trended versus random and AR(1). In addition to the classical t -test using the Ordinary Least Squares (OLS) estimator of the slope and its standard error, we consider seven t -tests with n-2\,\hbox{df} built on the Generalized Least Squares (GLS) estimator or an estimated GLS estimator, three variants of the classical t -test with different variances of the OLS estimator, two asymptotic tests built on the Maximum Likelihood (ML) estimator, the F -test for fixed effects based on the Restricted Maximum Likelihood (REML) estimator in the mixed-model approach, two t -tests with n - 2 df based on first differences (FD) and first-difference ratios (FDR), and four modified t -tests using various corrections of the number of degrees of freedom. The FDR t -test, the REML F -test and the modified t -test using Dutilleul's effective sample size are the most valid among the testing procedures that do not assume the complete knowledge of the covariance matrix of the errors. However, modified t -tests are not applicable and the FDR t -test suffers from a lack of power when the regressor is fixed and trended ( i.e. , FDR is the same as FD in this case when observations are equally spaced), whereas the REML algorithm fails to converge at small sample sizes. The classical t -test is valid when the regressor is fixed and trended and autocorrelation among errors is predominantly negative, and when the regressor is random and AR(1), like the errors, and autocorrelation is moderately negative or positive. We discuss the results graphically, in terms of the circularity condition defined in repeated measures ANOVA and of the effective sample size used in correlation analysis with autocorrelated sample data. An example with environmental data is presented.     

空气污染治理与公众健康———来自“大气十条”政策的证据

为探究《大气污染防治行动计划》 (以下简称“大气十条”)的健康效应,本文基于中国健康与营养调查(CHNS)数据及省级面板数据,利用基于多项Logit模型的双重差分法(Logit-DID),从微观与宏观两个维度考察“大气十条”政策的健康改善效应及其传导机制,并进一步通过异质性分析探讨环境健康不平等的内在原因 研究发现:“大气十条”实施带来显著的健康效应,该政策不仅能有效控制与空气污染高度相关疾病的发病率和死亡占比,还能够间接降低受空气污染影响较小的疾病病情。其作用机理主要通过控制PM2.5浓度改善公众健康,同时该政策对二氧化硫(SO2)、氮氧化物、烟(粉)尘等其 他污染物浓度的下降起到了协同作用。进一步分析显示环境福利不公平的现象依然存在,“大气十条”政 策显著降低了疾病高发人群的发病率,且对女性、城镇居民和低、高年龄段等疾病高发人群的健康影响更显著。本文为政府构建环境健康公平发展路径,推进“健康中国”战略提供了经验证据和政策借鉴。     

Unconditional analogues of Cochran–Mantel–Haenszel tests

The Cochran–Mantel–Haenszel tests are a suite of tests that are usually defined as conditional tests, tests that assume all marginal totals are known before sighting the data. Here unconditional analogues of these tests are defined for the more usual situation when the marginal totals are not known before sighting the data.     

Multiple hypothesis tests based On conditional differences in means

Many hypothesis tests are univariate tests and cannot cope with multiple hypothesis without an auxiliary procedure as e. g. the Bonferroni-Holm-procedure. At the same time, there is an urgent need for testing multiple hypothesis due to the very simple existing methods as the Bonferroni-correction or the Bonferroni-Holm-procedure, which suffers from a very small local significance level to detect statistical inferences or the drawback that logical and statistical dependencies among the test statistics are not used, whereby its detection is NP-hard. In honour of this occasion, we present a multiple hypothesis test for i.i.d. random variables based on conditional differences in means, which is capable to cope with multiple hypothesis and does not suffer on such drawbacks as the Bonferroni-correction or the Bonferroni-Holm-procedure. Thereby, the computation time can be neglected.     

Analysis of robust design experiments with time-dependent ordinal response characteristics: a quality improvement study from the horticulture industry

An approach to the analysis of time-dependent ordinal quality score data from robust design experiments is developed and applied to an experiment from commercial horticultural research, using concepts of product robustness and longevity that are familiar to analysts in engineering research. A two-stage analysis is used to develop models describing the effects of a number of experimental treatments on the rate of post-sales product quality decline. The first stage uses a polynomial function on a transformed scale to approximate the quality decline for an individual experimental unit using derived coefficients and the second stage uses a joint mean and dispersion model to investigate the effects of the experimental treatments on these derived coefficients. The approach, developed specifically for an application in horticulture, is exemplified with data from a trial testing ornamental plants that are subjected to a range of treatments during production and home-life. The results of the analysis show how a number of control and noise factors affect the rate of post-production quality decline. Although the model is used to analyse quality data from a trial on ornamental plants, the approach developed is expected to be more generally applicable to a wide range of other complex production systems.     

4-6岁幼儿电子游戏卷入度与得分关系研究

为了解4-6岁幼儿电子游戏卷入度与游戏得分的关系,对随机选取的20名4-6岁的幼儿在选用的电子游戏中的行为表现及游戏得分进行了观察研究。结果发现: （1）电子游戏卷入度的正性维度得分（M=37.750）高于负性维度得分（M=23.600）;（2）游戏得分从高到低的项目为：保卫萝卜（M=3.200）>水果消消乐（M=2.400）>俄罗斯方块（M=1.400）;（3）电子游戏卷入度负性因子与游戏得分的交互作用明显,F(6,14)=14.368,P<0.005。结论：（1）益智电子游戏可以较好促进4-6岁幼儿产生喜悦、注意、鼓励、努力等积极情绪;（2）游戏规则和操作越简单,越容易成功的益智游戏,更容易吸引4-6岁幼儿;（3）场景多变性、任务挑战难度越大的益智游戏,具有双刃剑的效应,虽然可以引起4-6岁幼儿参与游戏的兴趣,但是也容易给他们带来消极的情感体验。     

贾平凹与池莉作品中女性形象之比较

贾平凹和池莉塑造的女性形象具有很大的差异性,这种差异性的出现,反映了男性本位主义立场与女性本位主义立场的矛盾。贾平凹的作品体现了很浓重的男权意识,作品中的女主人公或被男性欣赏,或依附于男性,她们无论被作者赋予怎样的性格与命运,最终都失去了自我的主体性。而池莉作为新写实派的代表人物,文学创作比较贴近现实生活,她的作品多是从女性视角出发,用自身独特的感受来描写作品中的女性人物形象,描画她们勇于同命运抗争的自主性格和自主意识。