Asset Details
Do you wish to reserve the book?
Where Do We Go from Here? Nonresponse and Social Measurement
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Where Do We Go from Here? Nonresponse and Social Measurement
Do you wish to request the book?
Where Do We Go from Here? Nonresponse and Social Measurement
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Where Do We Go from Here? Nonresponse and Social Measurement
2013
Overview
Surveys undergird government statistical systems and social scientific research throughout the world. Rates of nonresponse are rising in cross-sectional surveys (those conducted during a fixed period of time and not repeated). Although this trend worries those concerned with the validity of survey data, there is no necessary relationship between the rate of nonresponse and the degree of bias. A high rate of nonresponse merely creates the potential for bias, but the degree of bias depends on how factors promoting nonresponse are related to variables of interest. Nonresponse can be reduced by offering financial incentives to respondents and by careful design before entering the field, creating a trade-off between cost and potential bias. When bias is suspected, it can be countered by weighting individual cases by the inverse of their response propensity. Response propensities are typically estimated using a logistic regression equation to predict the dichotomous outcome of survey participation as a function of auxiliary variables. The Multi-level Integrated Database Approach employs multiple databases to collect as much information as possible about the target sample during the initial sampling stage and at all possible levels of aggregation to maximize the accuracy of estimated response propensities.
