Nowadays, internet-based surveys are increasingly used for data collection, because their usage is simple and cheap. Also they give fast access to a large group of respondents. There are many factors affecting interne...Nowadays, internet-based surveys are increasingly used for data collection, because their usage is simple and cheap. Also they give fast access to a large group of respondents. There are many factors affecting internet surveys, such as measurement, survey design and sampling selection bias. The sampling has an important place in selection bias in internet survey. In terms of sample selection, the type of access to internet surveys has several limitations. There are internet surveys based on restricted access and on voluntary participation, and these are characterized by their implementation according to the type of survey. It can be used probability and non-probability sampling, both of which may lead to biased estimates. There are different ways to correct for selection biases;poststratification or weighting class adjustments, raking or rim weighting, generalized regression modeling and propensity score adjustments. This paper aims to describe methodological problems about selection bias issues and to give a review in internet surveys. Also the objective of this study is to show the effect of various correction techniques for reducing selection bias.展开更多
文摘Nowadays, internet-based surveys are increasingly used for data collection, because their usage is simple and cheap. Also they give fast access to a large group of respondents. There are many factors affecting internet surveys, such as measurement, survey design and sampling selection bias. The sampling has an important place in selection bias in internet survey. In terms of sample selection, the type of access to internet surveys has several limitations. There are internet surveys based on restricted access and on voluntary participation, and these are characterized by their implementation according to the type of survey. It can be used probability and non-probability sampling, both of which may lead to biased estimates. There are different ways to correct for selection biases;poststratification or weighting class adjustments, raking or rim weighting, generalized regression modeling and propensity score adjustments. This paper aims to describe methodological problems about selection bias issues and to give a review in internet surveys. Also the objective of this study is to show the effect of various correction techniques for reducing selection bias.
