选择(遗传算法)
加权
计算机科学
互联网
数据收集
选择偏差
数据科学
Web应用程序
网络调查
视力
万维网
情报检索
统计
机器学习
数学
医学
天文
物理
放射科
标识
DOI:10.1111/j.1751-5823.2010.00112.x
摘要
Summary At first sight, web surveys seem to be an interesting and attractive means of data collection. They provide simple, cheap, and fast access to a large group of potential respondents. However, web surveys are not without methodological problems. Specific groups in the populations are under‐represented because they have less access to Internet. Furthermore, recruitment of respondents is often based on self‐selection. Both under‐coverage and self‐selection may lead to biased estimates. This paper describes these methodological problems. It also explores the effect of various correction techniques (adjustment weighting and use of reference surveys). This all leads to the question whether properly design web surveys can be used for data collection. The paper attempts to answer this question. It concludes that under‐coverage problems may solve itself in the future, but that self‐selection leads to unreliable survey outcomes.
科研通智能强力驱动
Strongly Powered by AbleSci AI