Polynomial regression with errors in the variables

A polynomial functional relationship with errors in both variables can be consistently estimated by constructing an ordinary least squares estimator for the regression coefficients, assuming hypothetically the latent true regressor variable to be known, and then adjusting for the errors. If normality of the error variables can be assumed, the estimator can be simplified considerably. Only the variance of the errors in the regressor variable and its covariance with the errors of the response variable need to be known. If the variance of the errors in the dependent variable is also known, another estimator can be constructed.     

Scaling unobservable constructs in social science

The use of the logit–probit model for constructing social measurement scales is explored by using two data sets. The first was specifically designed for scaling and consists of answers by 1490 individuals to five questions on economic self-determination. The second is from the Workplace Industrial Relations Survey and relates to answers to six questions addressed to 1005 firms about innovations. It is shown that although scales can be constructed their precision (reliability) is likely to be low. Further, for examples like these, latent class models may give an equally satisfactory account of the data.     

不完全市场经济条件下我国企业合并会计处理方法选择

2006年财政部颁布了38项具体会计准则,新准则在充分结合目前我国会计环境的基础上,实现了与国际惯例的趋同。文中在阐述我国不完全市场经济的基础上,深入分析了新会计准则在企业合并中会计处理方法的选择,对权益结合法和购买法进行了对比分析,并进一步给出了企业合并会计处理方法选择方面的建议。     

Delphi应用程序中模糊查询和组合查询的实现

本文叙述了ＭＩＳ中模糊查询和组合查询的基本概念，介绍了利用Ｄｅｌｐｈｉ 的Ｑｕｅｒｙ 元件实现模糊查询和组合查询的方法，并以一个实际例子加以说明．     

Regression calibration for logistic regression with multiple surrogates for one exposure

Methods have been developed by several authors to address the problem of bias in regression coefficients due to errors in exposure measurement. These approaches typically assume that there is one surrogate for each exposure. Occupational exposures are quite complex and are often described by characteristics of the workplace and the amount of time that one has worked in a particular area. In this setting, there are several surrogates which are used to define an individual's exposure. To analyze this type of data, regression calibration methodology is extended to adjust the estimates of exposure-response associations for the bias and additional uncertainty due to exposure measurement error from multiple surrogates. The health outcome is assumed to be binary and related to the quantitative measure of exposure by a logistic link function. The model for the conditional mean of the quantitative exposure measurement in relation to job characteristics is assumed to be linear. This approach is applied to a cross-sectional epidemiologic study of lung function in relation to metal working fluid exposure and the corresponding exposure assessment study with quantitative measurements from personal monitors. A simulation study investigates the performance of the proposed estimator for various values of the baseline prevalence of disease, exposure effect and measurement error variance. The efficiency of the proposed estimator relative to the one proposed by Carroll et al. [1995. Measurement Error in Nonlinear Models. Chapman & Hall, New York] is evaluated numerically for the motivating example. User-friendly and fully documented Splus and SAS routines implementing these methods are available (http://www.hsph.harvard.edu/faculty/spiegelman/multsurr.html).     

Polynomial Regression and Estimating Functions in the Presence of Multiplicative Measurement Error

We consider the polynomial regression model in the presence of multiplicative measurement error in the predictor. Two general methods are considered, with the methods differing in their assumptions about the distributions of the predictor and the measurement errors. Consistent parameter estimates and asymptotic standard errors are derived by using estimating equation theory. Diagnostics are presented for distinguishing additive and multiplicative measurement error. Data from a nutrition study are analysed by using the methods. The results from a simulation study are presented and the performances of the methods are compared.     

抗坏血酸常用测定方法探讨

抗坏血酸是某些食品尤其是果蔬及其制品质量的重要参数之一。本文主要介绍了果蔬及其制品抗坏血酸的常用分析方法,阐述了不同分析方法的特点及其优缺点,为测定抗坏血酸选择合适的方法提供了一些参考。     

测量不确定度的评定与表示

测量不确定度如何正确评定与表示，是个极其重要的问题，通过实例介绍了不确定度的有关概念，给出了标准不确定度A类、B类评定的方法，以及标准不确定度的合成方法与展伸不确定度。     

波普尔境况分析方法述评

波普尔的境况分析方法直接源于经济学的“零点法”,其实质就是运用“批判理性主义”原则对人的行为进行客观理解。境况分析方法是自主的解释性社会科学研究人类行为“未预期后果”的基本方法。虽然波普尔对马克思主义怀有某种“敌意”,但其境况分析方法事实上就是马克思主义一般社会历史条件分析方法的具体化、境况化。     

Implementation of ridge analysis on quadratic response surfaces

A computer program that performs ridge analysis on quadratic response surfaces is presented in this paper, the primary goal of which is to seek the estimated optimum operating conditions inside a spherical region of experimentation during the stage of process optimization. The computational algorithm is developed based upon the trust-region methods in nonlinear optimization and guarantees the resulting operating conditions to be globally optimal without any priori assumption on the structure of response functions. Under a particular condition termed the "hard case" arising from the trust region literature, the conventional ridge analysis procedure fails to provide a set of acceptable optimum operating settings, yet the proposed algorithm has the capability of locating a pair of non-unique global solutions achieved on an identical estimated response value. Two illustrative examples taken from the response surface methodology (RSM) literature are given to demonstrate the effectiveness and efficiency of the method addressed in the paper.