Open Access Highly Accessed Debate

Should researchers use single indicators, best indicators, or multiple indicators in structural equation models?

Leslie A Hayduk1* and Levente Littvay2

Author affiliations

1 Department of Sociology, University of Alberta, Edmonton, Alberta, T6G 2H4, Canada

2 Department of Political Science, Central European University, Nador u. 9, Budapest, H-1051, Hungary

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Citation and License

BMC Medical Research Methodology 2012, 12:159  doi:10.1186/1471-2288-12-159

Published: 22 October 2012



Structural equation modeling developed as a statistical melding of path analysis and factor analysis that obscured a fundamental tension between a factor preference for multiple indicators and path modeling’s openness to fewer indicators.


Multiple indicators hamper theory by unnecessarily restricting the number of modeled latents. Using the few best indicators – possibly even the single best indicator of each latent – encourages development of theoretically sophisticated models. Additional latent variables permit stronger statistical control of potential confounders, and encourage detailed investigation of mediating causal mechanisms.


We recommend the use of the few best indicators. One or two indicators are often sufficient, but three indicators may occasionally be helpful. More than three indicators are rarely warranted because additional redundant indicators provide less research benefit than single indicators of additional latent variables. Scales created from multiple indicators can introduce additional problems, and are prone to being less desirable than either single or multiple indicators.

Single indicators; Factor analysis; Multiple indicators; Testing; Structural equation model