Donald Trump won the 2024 US Presidential Election despite polls predicting a Democratic lead, echoing the polling miss in 2016. Using the data defect correlation framework, we revisit the 60,000-respondent Cooperative Election Study and find that non-response bias for Trump voters persists on the same order of magnitude ($ρ=-0.0030$ vs $-0.0045$ in 2016) even under sample-matching to the US adult population. We additionally find evidence of positive response bias for Harris voters after adjusting for turnout. Consistent with findings in 2016, polling errors scale with state population size, and larger samples produce greater departures from conventional confidence intervals, with reductions of effective sample size exceeding 99% in the largest states. We propose a pre-election bias correction estimator informed by historical data defect correlations and turnout rates that decreases RMSE from 0.13 to 0.05 using only prior election data, comparable to post-election weighting (RMSE 0.09).

翻译：唐纳德·特朗普赢得2024年美国总统选举，尽管民调预测民主党领先，重演了2016年民调失准的情况。利用数据缺陷相关性框架，我们重新审视了包含6万名受访者的合作选举研究，发现即使采用与美国成年人口样本匹配的方法，特朗普选民的无应答偏差仍维持在同等量级（ρ=-0.0030，对比2016年-0.0045）。此外，在调整投票率后，我们发现哈里斯选民存在正向应答偏差的证据。与2016年研究结果一致，民调误差随州人口规模扩大而增加，且样本量越大，偏离传统置信区间的程度越高，最大州的样本有效规模缩减幅度超过99%。我们提出一种基于历史数据缺陷相关性和投票率的选前偏差校正估计量，仅使用前期选举数据即可将均方根误差从0.13降至0.05，其表现与选后加权（均方根误差0.09）相当。