Survey methodology field is experiencing challenging expansion – Web surveys. The Web is currently changing the structure of everyday communication, and the survey field is catching this trend by pervasively adopting the Web as a data collection mode. Popularity of Web surveys and increasing demands for well-established Web survey methodology have triggered researchers’ inquisitiveness to explore the Web as a survey mode. Unfortunately, the development of Web survey methodology does not seem to meet its demands, and most existing methodological Web survey studies are heavily focused on the aspects of questionnaire design and usability. While findings from those studies are helpful in improving the Web survey design features, their implications for survey inferences are limited, because of their qualitative nature. Missing from the current literature are statistical improvement of Web survey data. Propensity score adjustment has been suggested as an alternative for statistically surmounting inherent problems in Web surveys. However, the link between Web surveys and propensity score adjustment is not well understood as studies that have examined the performance of propensity score adjustment do not seem to document the statistical procedures or to clearly address the scope of adjustment. Moreover, there has been a minimal amount of evidence for its performance, and the implications are inconclusive. This study attempts to investigate the propensity score adjustment for Web surveys academically. It will first provide a clear description of application procedures of propensity score adjustment for Web survey data by presenting Web survey protocols and stages of correction. Then, it will explore the applicability of propensity score adjustment by focusing on volunteer panel Web surveys by comparing the performance of different weighting schemes with respect to bias reduction.