Abstract
The use of the sampling weights when fitting models to complex survey data is considered. It is shown that when the sample is selected with unequal selection probabilities that are related to the values of the response variables even after conditioning on all the available design information, ignoring the sample selection scheme in the inference process, can yield misleading results. Probability weighting of the sample observations yields consistent estimators of the model parameters and protects against model misspecification, although in a limited sense. Other methods of incorporating the sampling weights in the inference process are discussed and compared to the use of probability weighting.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
