Single and joint inclusion probabilities are generally available and known for complex survey designs up to the point where survey weights are modified due to nonresponse and population controls. Best practice by sophisticated survey practitioners generally includes weight modifications, first by calibration, ratio adjustment or raking to correct for nonresponse, next by further steps to impose...

AUTHOR’S NOTE: 7a~ ~-~<?/tJ ~c’M:’c/M’c/F~~, YcM~ycc~oM a~Dcw~ AUTHOR’S NOTE: I am grateful to Michael Flynn James Ja kson nd David Segal, principal investigators of he 1973 Detroit Area Study, for the use of their data. E. M. Beck read earlier drafts and provided invaluable assistance. My thanks also to Mary Senter, John Siebs, Connie Gask, Paula Sa, and Diane ~a/!~ /sc’ ~o ~f~ 5’~~ Y /!M 5’~&...

Traditional methods for sampling weight adjustment involve weighting class adjustment for nonresponse bias reduction, followed by post-stratification (raking-ratio or regression) adjustment for coverage bias reduction, and then trimming (or winsorization) of extreme weights for variance reduction followed by final post-stratification to meet desired control totals and for further variance reduc...

OBJECTIVES The goal of this article is to examine whether or not the results of the Queensland Community Engagement Trial (QCET)-a randomized controlled trial that tested the impact of procedural justice policing on citizen attitudes toward police-were affected by different types of nonresponse bias. METHOD We use two methods (Cochrane and Elffers methods) to explore nonresponse bias: First, ...

Survey nonresponse is a ubiquitous problem in modern survey research. As individuals have become less likely to respond to surveys there has been a simultaneous rise in highly granular data sources that can be used to help ameliorate the nonresponse problem. While much research has been done on post-hoc weighting methods, which provide a flexible and general solution for unit nonresponse, there...