Tracking Opinion over Time: A method for Reducing Sampling Error

Across a wide range of applications, the Kalman filtering and smoothing algorithm provides survey researchers with a single, systematic technique by which to generate four kinds of useful information. First, it enables survey analysts to differentiate between random sampling error and true opinion c...

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Bibliographic Details
Published in:Public opinion quarterly 1999-07, Vol.63 (2), p.178-192
Main Authors: GREEN, DONALD P., GERBER, ALAN S., BOEF, SUZANNA L. DE
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Data smoothing
Estimates
Kalman filters
Maximum likelihood estimation
Methodology
Noise
Opinion polls
Political attitudes
Political communication
Political partisanship
Political sociology
Polls
Polls & surveys
Public Opinion
Public opinion polls
Public opinion surveys
Samples
Sampling error
Sampling errors
Sociology
Software
Standard error
Statistical analysis
Statistical variance
Studies
Surveys
Trends
Citations: Items that cite this one
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Description
Summary:Across a wide range of applications, the Kalman filtering and smoothing algorithm provides survey researchers with a single, systematic technique by which to generate four kinds of useful information. First, it enables survey analysts to differentiate between random sampling error and true opinion change. Second, Kalman smoothing provides a means by which to accumulate information across surveys, greatly increasing the precision with which public opinion is gauged at any given point in time. Third, this technique provides a rigorous means by which to interpolate missing observations and calculate the uncertainty associated with these interpolations. Finally, the Kalman algorithm improves the accuracy with which public opinion may be forecasted. Our empirical examples, which focus on party identification, show that the Kalman algorithm can dramatically reduce sampling error in survey data. Since soft-ware implementing this technique is readily available, survey analysts are encouraged to use it to make more efficient use of the data at their disposal.
ISSN:0033-362X
1537-5331
DOI:10.1086/297710