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Evaluating the risk of nonresponse bias in educational large-scale assessments with school nonresponse questionnaires: a theoretical study

机译:用学校无应答问卷评估教育大规模评估中无应答偏差的风险:一项理论研究

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Abstract Survey participation rates can have a direct impact on the validity of the data collected since nonresponse always holds the risk of bias. Therefore, the International Association for the Evaluation of Educational Achievement (IEA) has set very high standards for minimum survey participation rates. Nonresponse in IEA studies varies between studies and cycles. School participation is at a higher risk relative to within-school participation; school students are more likely to cooperate than adults (i.e., university students or school teachers). Across all studies conducted by the IEA during the last decade, between 7 and 33% of participating countries failed to meet the minimum participation rates at the school level. Quantifying the bias introduced by nonresponse is practically impossible with the currently implemented design. During the last decade social researchers have introduced and developed the concept of nonresponse questionnaires. These are shortened instruments applied to nonrespondents, and aim to capture information that correlates with both: survey’s main outcome variable(s), and respondent’s propensity of participation. We suggest in this paper a method to develop such questionnaires for nonresponding schools in IEA studies. By these means, we investigated school characteristics that are associated with students’ average achievement scores using correlational and multivariate regression analysis in three recent IEA studies. We developed regression models that explain with only 11 school questionnaire variables or less up to 77% of the variance of the school mean achievement score. On average across all countries, the R _(2) of these models was 0.24 (PIRLS), 0.34 (TIMSS, grade 4) and 0.36 (TIMSS grade 8), using 6–11 variables. We suggest that data from such questionnaires can help to evaluate bias risks in an effective way. Further, we argue that for countries with low participation rates a change in the approach of computing nonresponse adjustment factors to a system were school′s participation propensity determines the nonresponse adjustment factor should be considered.
机译:摘要调查参与率可能直接影响收集到的数据的有效性,因为无响应始终存在偏差的风险。因此,国际教育成就评估协会(IEA)为最低调查参与率设定了很高的标准。 IEA研究中的无反应在研究和周期之间有所不同。相对于校内参与,学校参与的风险更高;与成年人(即大学生或学校教师)相比,在校学生更容易合作。在过去十年中,IEA进行的所有研究中,有7%至33%的参与国未能达到学校一级的最低参与率。使用当前实现的设计,几乎不可能量化无响应引起的偏差。在过去的十年中,社会研究人员引入并发展了无应答问卷的概念。这些是缩短的工具,适用于未回答者,旨在捕获与以下两项相关的信息:调查的主要结果变量和回答者的参与倾向。我们建议在本文中提供一种方法,为IEA研究中的无反应学校开发此类问卷。通过这些方法,我们在三项IEA最新研究中使用相关和多元回归分析,调查了与学生平均成绩得分相关的学校特征。我们开发了回归模型,该模型仅用11个学校问卷调查变量或以下变量进行解释,最多可解释学校平均成就分数方差的77%。在所有国家中,使用6-11个变量,这些模型的R _(2)平均为0.24(PIRLS),0.34(TIMSS,4级)和0.36(TIMSS 8级)。我们建议,此类问卷的数据可以帮助以有效方式评估偏差风险。此外,我们认为,对于参与率较低的国家,在学校的参与倾向确定应考虑无响应调整因子的情况下,对系统计算无响应调整因子的方法发生了变化。

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