Collecting survey data in Japan and the USA is difficult for many reasons, including the difficulty of creating complete sampling frames and low response rates. Online surveys, which collect data through online access panels and recruit members using nonprobability sampling, is becoming a popular alternative to traditional survey techniques, both in market and social science research. However, sociological researchers are hesitant to adopt online survey data collection techniques as it is unclear how representative such data are. This article examines the quality of online survey data by comparing online surveys with the two datasets collected using probability sampling, the American Community Survey and the General Social Survey. We conducted univariate, bivariate, and multivariate analyses and investigated whether similarities improve from the univariate analyses to bivariate relationships, and to bivariate relationships with controls. The results show that similarities improved from univariate to bivariate and multivariate analyses, but the results of bivariate and multivariate analyses did not differ. We concluded that data collected via volunteer-based access panels yielded similar results to the benchmark data, especially when the relationships among variables are examined. We argue that automatically discrediting the data collected via volunteer-based access panels is not good practice. With careful considerations of data quality, online survey data with nonprobability sampling could advance sociological research by giving researchers more freedom to ask questions at a relatively low cost, with a quick turnaround time, and more opportunities to conduct cross-national research.

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评估 2018 年在美国收集的在线调查数据的质量：单变量、双变量和多变量分析

在日本和美国收集调查数据很困难，原因有很多，包括难以创建完整的抽样框架和低响应率。通过在线访问面板收集数据并使用非概率抽样招募成员的在线调查正在成为市场和社会科学研究中传统调查技术的流行替代方法。然而，社会学研究人员对采用在线调查数据收集技术犹豫不决，因为尚不清楚这些数据的代表性。本文通过将在线调查与使用概率抽样收集的两个数据集（美国社区调查和一般社会调查）进行比较来检验在线调查数据的质量。我们进行了单变量、双变量、和多变量分析，并研究了从单变量分析到双变量关系以及与对照的双变量关系的相似性是否得到改善。结果表明，从单变量到双变量和多变量分析的相似性有所提高，但双变量和多变量分析的结果没有差异。我们得出的结论是，通过基于志愿者的访问面板收集的数据与基准数据产生了相似的结果，尤其是在检查变量之间的关系时。我们认为，自动抹黑通过基于志愿者的访问面板收集的数据并不是好的做法。通过仔细考虑数据质量，具有非概率抽样的在线调查数据可以通过给予研究人员更多的自由以相对较低的成本提出问题来推进社会学研究，