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测量误差问题：原子弹幸存者辐射剂量反应分析的启示AI 解读

Some basic issues in the errors-in-variables problem are discussed, in terms of considerations that arose in analyses of radiation effects on atomic bomb survivors. The setting essentially involves generalized linear models for the response variables, a very nonnormal distribution of the true covariable, and multiplicative errors in the observed covariable. Consideration is given to distinctions between structural and functional modeling. It is argued that careful attention…

测量误差诊断与性别歧视问题AI 解读

Numerical and graphical diagnostic tools are presented for studying the effect of explanatory-variable measurement errors on regression results when very rough knowledge about the measurement-error variances or reliabilities is available. These methods are exhibited on an example of sex discrimination in which male and female salaries are compared after adjustment for individual qualifications but the observed qualification variables are only proxies for what is actually…

广义线性模型中的协变量测量误差AI 解读

The EM algorithm is used to obtain estimators of regression coefficients for generalized linear models with canonical link when normally distributed covariates are masked by normally distributed measurement errors. By casting the true covariates as ‘missing data’, the EM procedure suggests an iterative scheme in which each cycle consists of an E-step, requiring the computation of approximate first and second conditional moments of the true covariates given the observed data,…

广义线性模型中的协变量测量误差AI 解读

The EM algorithm is used to obtain estimators of regression coefficients for generalized linear models with canonical link when normally distributed covariates are masked by normally distributed measurement errors. By casting the true covariates as ‘missing data’, the EM procedure suggests an iterative scheme in which each cycle consists of an E-step, requiring the computation of approximate first and second conditional moments of the true covariates given the observed data,…

广义线性模型中的残差AI 解读

Generalized linear models are regression-type models for data not normally distributed, appropriately fitted by maximum likelihood rather than least squares. Typical examples are models for binomial or Poisson data, with a linear regression model for a given, ordinarily nonlinear, function of the expected values of the observations. Use of such models has become very common in recent years, and there is a clear need to study the issue of appropriate residuals to be used for…

变量含误差模型中测量误差信息的组合AI 解读

For the regression model in which an explanatory variable contains measurement error, the instrumental variable and the correction for attenuation estimators of slope are considered. Although each requires extra information that is rarely available in ideal form, examinations of asymptotic variances and simulation results suggest that the correction for attenuation performs as well as a fairly strong instrumental variable when the measurement errors are not too large, and…

变量测量误差模型中测量误差信息的结合AI 解读

For the regression model in which an explanatory variable contains measurement error, the instrumental variable and the correction for attenuation estimators of slope are considered. Although each requires extra information that is rarely available in ideal form, examinations of asymptotic variances and simulation results suggest that the correction for attenuation performs as well as a fairly strong instrumental variable when the measurement errors are not too large, and…