模型答案概率能否代表调查人群？Jev 调查仿真中的条件预测与联合有效性研究

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Abstract:Survey simulations require realistic combinations of answers, but predictive accuracy alone does not establish that a model can generate them. We evaluate the option probabilities returned by Jev, a TypeSafe decision model, using linked responses to 20 binary items from five archived survey waves. We compare population-only prediction, prediction given recorded answers, and sequential completion that uses generated answers to predict later responses. Joint comparisons hold the starting population information fixed, and two three-question cases are completed in both question orders. We evaluate predictive scores, answer frequencies, and associations against the survey records. Recorded answers can improve predictive scores while associations remain distorted. Large conditional errors also occur. For example, among men who described themselves as having traditional values, the model predicted that 16% would see men and women as similar in workplace abilities, compared with 56% in the survey. Sequential completion has mixed effects on joint validity, and reversing question order produces different joint distributions in both tested cases. Order checks and classical marginal bounds clarify what can be assessed before linked validation answers are available. The findings support validating the joint events a simulation uses and separating empirical constraints from model assumptions. The evidence concerns selected binary tasks and one model version.

Subjects:	Applications (stat.AP); Artificial Intelligence (cs.AI); Computers and Society (cs.CY)
Cite as:	arXiv:2611.15576 [stat.AP]
	(or arXiv:2611.15576v1 [stat.AP] for this version)
	https://doi.org/10.48550/arXiv.2611.15576 arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Zengqing Wu [view email]
[v1] Wed, 11 Nov 2026 14:59:43 UTC (89 KB)