Trend Analysis with Pooled Data from Different Survey Series: The Latent Attitude Method

Donghui Wang, Yu Xie, Junming Huang

Research output: Contribution to journalArticlepeer-review


The use of pooled data from different repeated survey series to study long-term trends is handicapped by a measurement difficulty: different survey series often use different scales to measure the same attitude and thus generate scale-incomparable data. In this article, the authors propose the latent attitude method (LAM) to address this scale-incomparability problem, on the basis of the assumption that attitudes measured by ordinal categories reflect a latent attitude with cut points. The method extends the latent variable method in the case of a single survey series to the case of multiple survey series and leverages overlapping years for identification. The authors first assess the validity of the method with simulated data. The results show that the method yields accurate estimates of mean attitudes and cut point values. The authors then apply the method to an empirical study of Americans’ attitudes toward China from 1974 to 2019.

Original languageEnglish (US)
Pages (from-to)118-141
Number of pages24
JournalSociological Methodology
Issue number1
StatePublished - Feb 2024

All Science Journal Classification (ASJC) codes

  • Sociology and Political Science


  • attitudes toward China
  • incomparable scaling
  • interval scale
  • latent variable approach
  • ordinal scale
  • pooled survey series


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