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.
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