Public Opinion Quarterly - Advance Access

Alec M. Gallup, 1928-2009

Newport, F. — Fri, 20 Nov 2009 09:00:43 PST

Seth Masket. No Middle Ground: How Informal Party Organizations Control Nominations and Polarize Legislatures

Levendusky, M. S. — Mon, 09 Nov 2009 20:04:16 PST

Christopher Gelpi, Peter D. Feaver, and Jason Reifler. Paying the Human Costs of War: American Public Opinion and Casualties in Military Conflicts

Aday, S. — Sat, 07 Nov 2009 08:21:51 PST

Composite Estimates from Incomplete and Complete Frames for Minimum-Mse Estimation in a Rare Population: An Application to Families with Young Children

Ghosh-Dastidar, B., Elliott, M. N., Haviland, A. M., Karoly, L. A. — Tue, 03 Nov 2009 23:00:34 PST

Random digit dialing (RDD) can be costly for a rare population, but inexpensive convenience samples are unrepresentative by themselves. We combine biased estimates from an incomplete frame (a listed sample) with RDD estimates in a way that improves the accuracy (Mean Squared Error, MSE) of the RDD estimates compared to what would have been achieved without the incomplete frame data. Elliott and Haviland (2007) discuss this estimator when the bias of the incomplete frame estimator is known and discuss uncertainty in estimating bias; we describe an application that estimates incomplete frame bias relative to the RDD estimate for each parameter of interest, and conditions on that estimate. We discuss the extent to which this approach improves MSE relative to RDD alone and relative to a common alternative-stratified estimation based on whether a case appears in the incomplete frame. We surveyed 1,002 RDD and 1,023 listed households and examined the impact of incorporating listed estimates on MSE. Conditional on the bias estimate, MSE improved substantially for many outcomes because the estimated bias of listed sample estimates relative to RDD was small for most outcomes. For thirty-eight of forty-one estimates, including the listed sample (doubling the nominal sample size) produced MSEs equivalent to RDD sample sizes 1.22–1.85 times as large as the actual RDD sample size. Because the cost per listed complete was 20 percent of the cost per RDD complete, cost per effective sample size decreased relative to RDD alone for all but three estimates.

The Dynamics of Party Identification Reconsidered

Clarke, H. D., McCutcheon, A. L. — Wed, 02 Sep 2009 03:17:34 PDT

This paper uses mixed Markov latent class models and data from multiwave national panel surveys to investigate the stability of individual-level party identification in three Anglo-American democracies—the United States, Britain, and Canada. Analyses reveal that partisan attachments exhibit substantial dynamism at the latent variable level in the American, British, and Canadian electorates. Large-scale partisan dynamics are not a recent development; rather, they are present in all of the national panel surveys conducted since the 1950s. In all three countries, a generalized "mover–stayer" model outperforms rival models including a partisan stability model and a "black–white" nonattitudes model that specifies random partisan dynamics. The superiority of generalized mover–stayer models of individual-level party identification comports well with American and British studies that document nonstationary, long memory in macropartisanship. The theoretical perspective provided by party identification updating models is consistent with the mix of durable and flexible partisans found in the United States and elsewhere.

Not All Survey Effort is Equal: Reduction of Nonresponse Bias and Nonresponse Error

Peytchev, A., Baxter, R. K., Carley-Baxter, L. R. — Wed, 02 Sep 2009 03:17:33 PDT

Nonexperimental and experimental studies have shown a lack of association between survey effort and nonresponse bias. This does not necessarily mean, however, that additional effort could not reduce nonresponse bias. Theories on nonresponse would suggest the use of different recruiting methods for additional survey effort in order to address nonresponse bias. This study looks at changes in survey estimates as a function of making additional calls under the same protocol and additional calls under a different protocol. Respondents who were interviewed as a result of more than five call attempts were not significantly different on any of the key survey variables than those interviewed with fewer than five calls. Those interviewed under a different survey protocol, however, were different on 5 of 12 measures. Additional interviews under both the same and different protocols contributed to the reduction of total nonresponse error. In sum, the use of multiple protocols for part of the survey effort increased the response rate, changed point estimates, and achieved lower total nonresponse error. Future work is needed on optimizing survey designs that implement multiple survey protocols.