IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v19y1990i1p3-66.html
   My bibliography  Save this article

Simulation Studies of the Reliability of Computer-Aided Model Specification Using the TETRAD II, EQS, and LISREL Programs

Author

Listed:
  • PETER SPIRTES

    (Carnegie-Mellon University)

  • RICHARD SCHEINES

    (Carnegie-Mellon University)

  • CLARK GLYMOUR

    (Carnegie-Mellon University)

Abstract

TETRAD II, a fully automated successor to the TETRAD program, is intended to aid in the respecification of underspecified linear causal models, or structural equation models. The performance of TETRAD II is compared with the automatic respecification procedures in the EQS and LISREL VI programs using 360 simulated data sets from nine different linear models containing “latent†or unmeasured variables. LISREL VI and EQS each output a single suggested model; TETRAD II outputs a small list of such models. For these cases, we find that the TETRAD II program, which uses graph algorithms and heuristic search techniques, is more reliable (although less precise) than either EQS or LISREL VI, which use numerical algorithms and beam search techniques. A detailed analysis of the reasons for these differences is offered. Contrary to those who dismiss automated search techniques as unreliable “ransacking†or “data mining,†TETRAD II provides correct information about the true model for 95% of the large sample data sets. The need for further simulation tests and the prospects for the development of automated techniques to aid in the initial specification of causal models for nonexperimental data are discussed.

Suggested Citation

  • Peter Spirtes & Richard Scheines & Clark Glymour, 1990. "Simulation Studies of the Reliability of Computer-Aided Model Specification Using the TETRAD II, EQS, and LISREL Programs," Sociological Methods & Research, , vol. 19(1), pages 3-66, August.
  • Handle: RePEc:sae:somere:v:19:y:1990:i:1:p:3-66
    DOI: 10.1177/0049124190019001001
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124190019001001
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0049124190019001001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Glymour, Clark & Spirtes, Peter, 1988. "Latent variables, causal models and overidentifying constraints," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 175-198.
    2. McPherson, J. Miller & Welch, Susan & Clark, Cal, 1977. "The Stability and Reliability of Political Efficacy: Using Path Analysis to Test Alternative Models," American Political Science Review, Cambridge University Press, vol. 71(2), pages 509-521, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Verbrugge, Randal & Zaman, Saeed, 2023. "The hard road to a soft landing: Evidence from a (modestly) nonlinear structural model," Energy Economics, Elsevier, vol. 123(C).
    2. Dennis J. Aigner, 1988. "Symposium on Econometric Methodology 1 On Econometric Methodology and the Search for Causal Laws," The Economic Record, The Economic Society of Australia, vol. 64(4), pages 323-326, December.
    3. Anne-Marie Aish & Karl Jöreskog, 1990. "A panel model for political efficacy and responsiveness: an application of LISREL 7 with weighted least squares," Quality & Quantity: International Journal of Methodology, Springer, vol. 24(4), pages 405-426, November.
    4. Alessio Moneta & Peter Spirtes, 2005. "Graph-Based Search Procedure for Vector Autoregressive Models," LEM Papers Series 2005/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Chen, Pu & Chihying, Hsiao, 2007. "Learning Causal Relations in Multivariate Time Series Data," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 1, pages 1-43.
    6. Alessio Moneta, 2003. "Graphical Models for Structural Vector Autoregressions," LEM Papers Series 2003/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. Yang, Jian, 2005. "International bond market linkages: a structural VAR analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 15(1), pages 39-54, January.
    8. Alan Acock & Harold Clarke, 1990. "Alternative measures of political efficacy: models and means," Quality & Quantity: International Journal of Methodology, Springer, vol. 24(1), pages 87-105, February.
    9. Chen, Pu, 2010. "A time series causal model," MPRA Paper 24841, University Library of Munich, Germany.
    10. Randal Verbrugge & Saeed Zaman, 2024. "Post‐COVID inflation dynamics: Higher for longer," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 871-893, July.
    11. John, Peter & Sjoberg, Fredrik M, 2020. "Partisan responses to democracy promotion – Estimating the causal effect of a civic information portal," World Development, Elsevier, vol. 130(C).
    12. Tyler J. VanderWeele & Stijn Vansteelandt, 2022. "A statistical test to reject the structural interpretation of a latent factor model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 2032-2054, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:somere:v:19:y:1990:i:1:p:3-66. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.