Aspects of Statistical Computing: What Packages for the 1980's Ought to Do

A wish list of desirable statistical computing capabilities is presented. This may help one question which of these capabilities can be satisfied by existing packages, which might be met through reasonable extensions to these packages, which might require substantial new development, and which ought to be supplied by the computing environment rather than the packages. These questions are explored, taking into account the nature of the statistical work and the choices presented by technology. Attention is given to the barriers to be overcome if future statistical packages are to take full advantage of new technology.     

Simple Counterexamples against the Conditionality Principle

The famous theorem of Birnbaum, stating that the likelihood principle follows from the conditionality principle together with the sufficiency principle, has caused much discussion among statisticians. Briefly, many writers dislike the consequences of the likelihood principle (among other things, confidence coefficients and levels of tests are dismissed as meaningless), but at the same time they feel that both the conditionality principle and the sufficiency principle are intuitively obvious. In the present article we give examples to show that the conditionality principle should not be taken to be of universal validity, and we discuss some consequences of these examples.     

Using regression mixture models with non-normal data: examining an ordered polytomous approach

Mild to moderate skew in errors can substantially impact regression mixture model results; one approach for overcoming this includes transforming the outcome into an ordered categorical variable and using a polytomous regression mixture model. This is effective for retaining differential effects in the population; however, bias in parameter estimates and model fit warrant further examination of this approach at higher levels of skew. The current study used Monte Carlo simulations; 3000 observations were drawn from each of two subpopulations differing in the effect of X on Y. Five hundred simulations were performed in each of the 10 scenarios varying in levels of skew in one or both classes. Model comparison criteria supported the accurate two-class model, preserving the differential effects, while parameter estimates were notably biased. The appropriate number of effects can be captured with this approach but we suggest caution when interpreting the magnitude of the effects.     

中国式现代化指数构建研究

开启全面建设社会主义现代化国家新征程是新时代的战略安排,是中国共产党确立的伟大目标。构建科学合理的中国式现代化指数及其评估指标体系,对以中国式现代化全面推进中华民族伟大复兴意义重大。结合中国式现代化的内涵及其五大特征,按照党的二十大报告的总体框架构建中国式现代化指数评估指标体系,指标体系共囊括“经济现代化”“科教现代化”“政治现代化”“法治现代化”“文化现代化”“社会现代化”“生态现代化”“国家安全、国防与军队现代化”“和平发展现代化”和“党的建设现代化”等10个一级指标,以及41个二级指标,分别从主观、客观两个维度设置130个三级基本指标和特色指标,进而深入分析指标的基本构成及测算方法等。中国式现代化指数系统回答了什么是中国式现代化,应该以什么样的标准或指标对中国式现代化进行测量。在此基础上,从中国式现代化建设成效、党委政府业绩考核等多个维度探讨中国式现代化指数的应用前景。     

学业质量增值评价数学模型的比较研究——以西部某区教育实证数据为例

增值评价是以学生成长为核心,以学校发展为目标的一种评价方式,可以更公平地评价学校效能。增值评价有多种数学模型,其中,与基于平均名次、基于标准分的两种模型相比,基于学生成长百分位和多层线性回归两种模型的优势在于能够避免优秀学生增值空间受限的问题。在多层线性回归模型中纳入学生性别、家庭社会经济地位指数等学校不可控的生源因素,可有效排除生源因素对学生的影响,更符合关注学校“净效能”的评价理念。     

卓越教师评价标准比较及启示

卓越教师评价标准的建立与实施对教师专业发展起着重要的引导作用。美国、英国、澳大利亚、中国香港等国家或地区的卓越教师评价体系,在教师的知识结构、能力结构、教学成果、社区服务等方面具有一些共同特征,同时在教师能力结构、价值导向等方面又有各自的侧重。卓越教师评价标准应进一步体现卓越教师的实践专长,突出卓越教师作为教学变革的领导者,强化其对卓越教师培养过程的助推功能。     

数学文化对小学生数学核心素养发展作用测评模型构建与实证研究

数学核心素养是学生经过数学学习后应具备的关键能力与必备品格。已有大量研究证实数学文化对学生的认知、情感、品格等方面具有积极影响。如何评价数学文化对小学生数学核心素养发展的作用,成为本文的主要研究问题。本文通过文献分析、抽样调查和探索性因素分析等,得出数学文化对小学生数学核心素养发展作用的三个维度：必备品格(X1)、关键能力(X2)、数学情感态度观念(X3),构建测评模型：Y=0.26X1+0.31X2+0.42X3;通过专家咨询、师生调查、课堂观察等方法与验证性因素分析,得出所构建的测评模型拟合度良好。该测评模型为数学文化对学生核心素养发展的作用提供借鉴和测评工具支持。     

Maximum Likelihood Estimation for Stochastic Differential Equations with Random Effects

Abstract. We consider N independent stochastic processes (X _i (t), t ∈ [0,T _i ]), i=1,…, N, defined by a stochastic differential equation with drift term depending on a random variable φ _i . The distribution of the random effect φ _i depends on unknown parameters which are to be estimated from the continuous observation of the processes X_i. We give the expression of the exact likelihood. When the drift term depends linearly on the random effect φ _i and φ _i has Gaussian distribution, an explicit formula for the likelihood is obtained. We prove that the maximum likelihood estimator is consistent and asymptotically Gaussian, when T _i =T for all i and N tends to infinity. We discuss the case of discrete observations. Estimators are computed on simulated data for several models and show good performances even when the length time interval of observations is not very large.     

On the recoding of continuous and bounded indexes to a binomial form: an application to quality-of-life scores

The statistical analysis of patient-reported outcomes (PROs) as endpoints has shown to be of great practical relevance. The resulting scores or indexes from the questionnaires used to measure PROs could be treated as continuous or ordinal. The goal of this study is to propose and evaluate a recoding process of the scores, so that they can be treated as binomial outcomes and, therefore, analyzed using logistic regression with random effects. The general methodology of recoding is based on the observable values of the scores. In order to obtain an optimal recoding, the evaluation of the recoding method is tested for different values of the parameters of the binomial distribution and different probability distributions of the random effects. We illustrate, evaluate and validate the proposed method of recoding with the Short Form-36 (SF-36) Survey and real data. The optimal recoding approach is very useful and flexible. Moreover, it has a natural interpretation, not only for ordinal scores, but also for questionnaires with many dimensions and different profiles, where a common method of analysis is desired, such as the SF-36.     

Development of an innovative process evaluation approach for the Families Improving Together (FIT) for weight loss trial in African American adolescents

This study demonstrates how a multi-theoretical, multilevel process evaluation was used to assess implementation of the Families Improving Together (FIT) for weight loss intervention. FIT is a randomized controlled trial evaluating a culturally tailored, motivational plus family-based program on weight loss in African American adolescents and their parents. Social Cognitive, Self Determination, Family Systems theories and cultural tailoring principles guided the conceptualization of essential elements across individual/family, facilitator, and group levels. Data collection included an observational rating tool, attendance records, and a validated psychosocial measure.ResultsAttendance records (0 = absent, 1 = present, criteria = ≥70%) indicated that 71.5% of families attended each session. The survey (1 = false, 6 = true, criteria = ≥4.5) indicated that participants perceived a positive group climate (M = 5.16, SD = 0.69). A trained evaluator reported that facilitator dose delivered (0 = no, 1 = yes, criteria = ≥75%) was high (99.6%), and fidelity (1 = none to 4 = all, criteria = ≥3) was adequate at facilitator (M = 3.63, SD = 0.41) and group levels (M = 3.35, SD = 0.49). Five cultural topics were raised by participants related to eating (n = 3) and physical activity (n = 2) behaviors and were integrated as part of the final curriculum.DiscussionResults identify areas for program improvement related to delivery of multi-theoretical and cultural tailoring elements. Findings may inform future strategies for implementing effective weight loss programs for ethnic minority families.