In order to reduce future dependence on foreign oil and emissions of CO2, how much would US households be willing to pay annually to support increased energy research and development (R&D) activities designed to replace fossil fuels? Does it matter whether the R&D includes nuclear energy options? We explore these questions using data from a unique set of national telephone and Internet surveys. Using a national advisory referendum format, the contingent valuation method is applied to estimate annual household willingness-to-pay (WTP) for US household support of a national Energy Research and Development Fund (ERDF) for investments in energy sources not reliant on fossil fuels. While accounting for the level of (un)certainty in voting responses, the WTP modeling includes a comparison of both classic maximum likelihood estimation (MLE) and Bayesian analysis. Evidence indicates that MLE and Bayesian analysis achieve similar statistical inference, while the Bayesian analysis provides a narrower confidence interval around estimated WTP.