Web Survey Bibliography
Title Tips and Tricks for Raking Survey Data (a.k.a. Sample Balancing)
Author Battaglia, M. P.; Izrael, D.; Hoaglin, D.C; Frankel, M. R.
Source AAPOR
Year 2004
Access date 13.05.2014
Full text
Abstract
A survey sample may cover segments of the target population
in proportions that do not match the proportions of those
segments in the population itself. The differences may arise,
for example, from sampling fluctuations, from nonresponse, or
because the sample design was not able to cover the entire
population. In such situations one can often improve the
relation between the sample and the population by adjusting
the sampling weights of the cases in the sample so that the
marginal totals of the adjusted weights on specified
characteristics agree with the corresponding totals for the
population. This operation is known as raking ratio estimation
(Kalton 1983), raking, or sample-balancing, and the
population totals are usually referred to as control totals.
Raking may reduce nonresponse and noncoverage biases, as
well as sampling variability. The initial sampling weights in
the raking process are often equal to the reciprocal of the
probability of selection and may have undergone some
adjustments for unit nonresponse and noncoverage. The
weights from the raking process are used in estimation and
analysis. The adjustment to control totals is sometimes
achieved by creating a cross-classification of the categorical
control variables (e.g., age categories x gender x race x
family-income categories) and then matching the total of the
weights in each cell to the control total. This approach,
however, can spread the sample thinly over a large number of
cells. It also requires control totals for all cells of the crossclassification.
Often this is not feasible (e.g., control totals
may be available for age x gender x race but not when those
cells are subdivided by family income). The use of marginal
control totals for single variables (i.e., each margin involves
only one control variable) often avoids many of these
difficulties. In return, of course, the two-variable (and higherorder)
weighted distributions of the sample are not required to
mimic those of the population. Raking (or sample-balancing)
usually proceeds one variable at a time, applying a
proportional adjustment to the weights of the cases that belong
to the same category of the control variable. Izrael et al.
(2000) introduced a SAS macro for raking (sometimes
referred to as the IHB raking macro) that combines simplicity
and versatility. More recently, the IHB raking macro has been
enhanced to increase its utility and diagnostic capability
(Izrael et al. 2004).
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Year of publication2004
Bibliographic typeJournal article
Web survey bibliography - 2004 (99)
- Questionnaire Design: How to Plan, Structure and Write Survey Material for Effective Market Research...; 2013; Brace, I.
- A study on tolerable waiting time: how long are Web users willing to wait?; 2004; Nah, F. F.-H.
- Snowball Sampling ; 2004; Berg, S.
- Usability Testing to Evaluate Computer-Assisted Instruments; 2004; Hansen, S. E.; Couper, M. P.
- Tips and Tricks for Raking Survey Data (a.k.a. Sample Balancing); 2004; Battaglia, M. P.; Izrael, D.; Hoaglin, D.C; Frankel, M. R.
- The Art & Science of Interpreting Market Research Evidence; 2004; Fletcher, J.; Smith, D.
- Statistical Design for Research; 2004; Kish, L.
- Results of an On-Line Survey of Patients with Hereditary Angioedema; 2004; Huang, S.-W.
- Understanding the effect of prizes on response rates; 2004; Porter, S. R., Whitcomb, M. E.
- Multiple surveys of students and survey fatigue; 2004; Porter, S. R., Whitcomb, M. E., Weitzer, W. H.
- Conducting longitudinal studies; 2004; Bauer, K. W.
- A Typology of Research Methods Within the Social Sciences; 2004; Beissel-Durrant, G.
- The Economist/YouGov Internet Presidential poll.; 2004; Fiorina, M., Krosnick, J. A.
- Using an access panel as a sampling frame for voluntary household surveys. Experiences from a pilot...; 2004; Korner, T., Nimmergut, A.
- Understanding the question-answer process; 2004; Bradburn, N. M.
- The illusion of public opinion: Fact and artifact in american public opinion polls; 2004; Bishop, G. F.
- On the primacy of affect in attitude-behavior research; 2004; Thomas, R. K., Schofield, C. M.
- Measuring expectations; 2004; Manski, C. F.
- Item response theory modelling for questionnaire evaluation; 2004; Reeve, B. B., Masse, L.
- Examining expert reviews as a pretest method; 2004; DeMaio, T., Landreth, A.
- EFAMRO - Quality standards for access panel - QSAP; 2004
- Developmnent and testing of web questionnaires; 2004; Baker, R. P., Crawford, S. D., Swinehart, J.
- An experiment in call scheduling; 2004; Cunningham, P., Martin, D., Brick, J. M.
- A Comparison of multi-Item Likert and Visual Analogue Scales for the assessment of transactionally defined...; 2004; Flynn, D., van Schaik, P., van Wersch, A.
- When the Ethic is Functional to the Method: The Case of E-Mail Qualitative Interviews; 2004; Olivero, N., Lunt, P.
- Virtual Research Ethics: A Content Analysis of Surveys and Experiments Online; 2004; Peden, B. F., Flashinski, D. P.
- How to conduct behavioral research over the Internet: A begginer s guide to HTML and CGI/Perl; 2004; Fraley, R. C.
- Propensity Score Adjustment As an Alternative Weighting Scheme for Web Survey Data; 2004; Lee, Su.
- The Prevalence of Wireless Substitution; 2004; Luke, J. V., Blumberg, S. J., Cynamon, M. C.
- The Impact of Wireless Substitution on Random-Digit-Dialed Health Surveys; 2004; Blumberg, S. J., Luke, J. V.
- Is It the Young and the Restless Who Only Use Cellular Phones?; 2004; Steeh, C. G.
- Cell Phone Owners and Usage Patterns; 2004; Tuckel, P. S., O’Neill, H.
- Will a "Perfect Storm" of Cellular-Linked Forces Sink RDD Sampling?; 2004; Lavrakas, P. J.
- A New Era for Telephone Surveys; 2004; Steeh, C. G.
- Web Search Savvy: Strategies and Shortcuts for Online Research; 2004; Friedman, B. G.
- Can Internet Surveys be Used for Social Surveys? : Results of an Experimental Study; 2004; Honda, N., Motokawa, A.
- Cooperation and Community on the Internet: Past Issues and Present Perspectives for theoretical-empirical...; 2004; Matzat, U.
- Response and Field Period Effects: The Effect of Time in Online Market Research and Consequences for...; 2004; Basso Larsen, R., Rathod, S.
- Statistical Estimation Methods in Volunteer Panel Web Surveys; 2004; Lee, Su.
- Instrument Design for a Blaise Multimode Web, CATI, and Paper Survey; 2004; Pierzchala, M., Wright, D., Wilson, Cl., Guerino, P.
- Design and Application of On-line Questionnaries: Experiences from Micronesia; 2004; O'Neill, J. G., Spennemann, D. H. R.
- Valuation of Natural Resource Improvements in the Adirondacks; 2004; Banzhaf, S., Burtraw, D., Evans, D., Krupnick A.
- Response latency as an indicator of optimizing. A study comparing job applicants and job incumbents...; 2004; Callegaro, M., Yang, Y., Bhola, D. S., Dillman, D. A.
- Fundamentals of Marketing Research; 2004; Smith, S. M., Albaum, G.
- Do print and Web surveys provide the same results?; 2004; Huang, H.-M.
- Will Web Surveys Ever Become Part of Mainstream Research?; 2004; Schonlau, M.
- Online or Not Online? A Comparison of Offline and Online Surveys Conducted in the Context of 2002 German...; 2004; Faas, T.
- Recruitment for online access panels; 2004; Goeritz, A.
- Does Voice Matter? An Interactive Voice Response (IVR) Experiment; 2004; Couper, M. P., Singer, E., Tourangeau, R.
- No calibration required. Expanding the use of on-line research for new initiatives; 2004; Rogers, G., Dierckx, J.-H.