Results for this survey are based on telephone interviews conducted under the direction of Princeton Survey Research Associates International among a national sample of 1,504 adults living in the continental United States, 18 years of age or older, from January 6-10, 2010 (1,000 respondents were interviewed on a landline telephone, and 504 were interviewed on a cell phone, including 201 who had no landline telephone). Both the landline and cell phone samples were provided by Survey Sampling International. Interviews were conducted in English and Spanish. For detailed information about our survey methodology, see

The combined landline and cell phone sample are weighted using an iterative technique that matches gender, age, education, race/ethnicity, region, and population density to parameters from the March 2009 Census Bureau’s Current Population Survey. The sample is also weighted to match current patterns of telephone status and relative usage of landline and cell phones (for those with both), based on extrapolations from the 2009 National Health Interview Survey. The weighting procedure also accounts for the fact that respondents with both landline and cell phones have a greater probability of being included in the combined sample and adjusts for household size within the landline sample. Sampling errors and statistical tests of significance take into account the effect of weighting.

The following table shows the error attributable to sampling that would be expected at the 95% level of confidence for different groups in the survey:

In addition to sampling error, one should bear in mind that question wording and practical difficulties in conducting surveys can introduce error or bias into
the findings of opinion polls.


A logistic regression analysis was conducted on the unweighted full sample (N=1504) to determine the independent impact of each of a series of factors on likelihood to participate in the Census. The dependent variable was intention to participate in the Census (coded as 1=definitely will participate, 0 otherwise). The independent or predictor variables were recoded as dummy variables (0 or 1) based on the standard analytical groups used in the bivariate analysis.

The predicted probability in the graphic shows the difference in probabilities for the various groups:
oAge: 50 and older minus 18-29
oParty: Democrat minus Republican
oEducation: College graduate minus high school or less
oIncome: Family income $75,000 or more minus less than $30,000
oEthnicity: Hispanic minus non-Hispanic
oRace: Non-Hispanic white minus non-Hispanic black
oGender: Women minus men
The likelihood ratio chi-square for the model is χ2=223.4, p=.000.

A second logistic regression model was conducted that also included the four knowledge questions (QC.7-QC.10) where the correct answer was coded as 1 and incorrect and don’t know responses were coded as 0. The likelihood ratio chi-square for the second model that included the demographic and knowledge variables is χ2=364.0, p=.000.