Paradata refers to survey variables which are not of direct interest themselves, but are related to the quality of data on survey variables which are of interest. We focus on a categorical paradata variable, which reflects the presence of measurement error in a variable of interest. We propose a quasi-score test of the hypothesis of no measurement error bias in the estimation of regression coefficients under models for paradata. We also propose a regression-based test, analogous to a simple test proposed by Fuller for instrumental variables. The methods developed can take account of a complex sampling design. In an application with data from the British Household Panel Survey, all tests provide clear evidence of measurement bias in the estimated coefficient of gross pay. In a simulation study, all tests have rejection rates close to the nominal level under the null hypothesis; the quasi-score tests display more power than the regression-based test. The size of the quasi-score test is shown to be robust to some forms of misspecification of the paradata model, both by a theoretical argument and in findings of the simulation study.

中文翻译：

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使用Paradata测试调查数据分析中的测量误差

Paradata指的是本身并不是直接关注的调查变量，但与感兴趣的调查变量的数据质量有关。我们关注分类的paradata变量，该变量反映了相关变量中存在测量误差。我们针对准数据模型下的回归系数估计，提出了没有测量误差偏差的假设的准得分检验。我们还提出了一种基于回归的检验，类似于富勒针对工具变量提出的简单检验。开发的方法可以考虑复杂的采样设计。在具有英国家庭面板调查数据的应用程序中，所有测试都提供了明显的证据，表明估计的总工资系数存在计量偏差。在模拟研究中 在原假设下，所有测试的拒绝率均接近标称水平；准得分测试比基于回归的测试显示出更多的功能。无论是从理论上还是从模拟研究的结果来看，准得分测试的大小都对某些形式的paradata模型的错误指定具有鲁棒性。