Workshop - Statistics are useless without suitable data: How to implement and assess for data quality

Assessing the quality of participants’ responses is a concern for researchers using survey designs. This concern is particularly important for online data collection. Respondents often fail to read questions, follow instructions, and provide careless answers. These inattentive responses may stem from a minimization of cognitive effort, and despite literature showing the damaging effects of these responses, this methodological aspect is often ignored. For example, it can lead to biased estimates, attenuation of relationships, and psychometric invalidity. In this workshop, we will explore what data-quality controls are, why you should care about them, and how to implement them. We will cover reverse scaling, consistency, instructional manipulation checks, response patterns, and timed responses with time for brainstorming of additional alternatives.

对参与者响应质量的评估是采用调查设计的学者所面临的一项挑战。这一挑战在在线数据收集领域尤为重要。受访者常常未能仔细阅读问题、遵循指示，以及提供草率的答案。这些疏忽的响应可能源于认知努力的降低，尽管文献表明这些响应具有破坏性影响，但这一方法论方面往往被忽视。例如，它可能导致估计偏差、关系减弱和心理学无效性。在本研讨会上，我们将探讨数据质量控制的本质、为何应当关注它们，以及如何实施它们。我们将涵盖反向标度、一致性、指导性操纵检查、响应模式和计时响应，并留有时间进行其他替代方案的头脑风暴。