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Ronald J. Schoenberg

Personal Details

First Name:Ronald
Middle Name:J.
Last Name:Schoenberg
Suffix:
RePEc Short-ID:psc142

Affiliation

University of Washington

http://www.washington.edu
USA, Seattle/Washington

Research output

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Jump to: Articles

Articles

  1. Schoenberg, Ronald, 1997. "Constrained Maximum Likelihood," Computational Economics, Springer;Society for Computational Economics, vol. 10(3), pages 251-266, August.
  2. Gerhard Arminger & Ronald Schoenberg, 1989. "Pseudo maximum likelihood estimation and a test for misspecification in mean and covariance structure models," Psychometrika, Springer;The Psychometric Society, vol. 54(3), pages 409-425, September.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Schoenberg, Ronald, 1997. "Constrained Maximum Likelihood," Computational Economics, Springer;Society for Computational Economics, vol. 10(3), pages 251-266, August.

    Cited by:

    1. Guohua Feng & Apostolos Serletis, 2009. "Efficiency, Technical Change, and Returns to Scale in Large U.S. Banks: Panel Data Evidence from an Output Distance Function Satisfying Theoretical Regularity," Monash Econometrics and Business Statistics Working Papers 5/09, Monash University, Department of Econometrics and Business Statistics.
    2. Robert F. Engle & Aaron D. Smith, 1999. "Stochastic Permanent Breaks," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 553-574, November.
    3. Ooms, M., 2008. "Trends in Applied Econometrics Software Development 1985-2008, an analysis of Journal of Applied Econometrics research articles, software reviews, data and code," Serie Research Memoranda 0021, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    4. P. S. Sephton, 2000. "Financial analysis package for GAUSS," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(4), pages 433-438.
    5. Jolynn Pek & Hao Wu, 2015. "Profile Likelihood-Based Confidence Intervals and Regions for Structural Equation Models," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 1123-1145, December.
    6. George Economides & Jim Malley & Apostolis Philippopoulos & Ulrich Woitek, 2003. "Electoral Uncertainty, Fiscal Policies & Growth: Theory and Evidence from Germany, the UK and the US," CESifo Working Paper Series 1072, CESifo Group Munich.

  2. Gerhard Arminger & Ronald Schoenberg, 1989. "Pseudo maximum likelihood estimation and a test for misspecification in mean and covariance structure models," Psychometrika, Springer;The Psychometric Society, vol. 54(3), pages 409-425, September.

    Cited by:

    1. Po-Hsien Huang & Hung Chen & Li-Jen Weng, 2017. "A Penalized Likelihood Method for Structural Equation Modeling," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 329-354, June.
    2. Paul Dudgeon, 2017. "Some Improvements in Confidence Intervals for Standardized Regression Coefficients," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 928-951, December.
    3. Haruhiko Ogasawara, 2000. "Some relationships between factors and components," Psychometrika, Springer;The Psychometric Society, vol. 65(2), pages 167-185, June.
    4. B. N. Sánchez & E. A. Houseman & L. M. Ryan, 2009. "Residual-Based Diagnostics for Structural Equation Models," Biometrics, The International Biometric Society, vol. 65(1), pages 104-115, March.
    5. Hildebrandt, Lutz & Görz, Nicole, 1999. "Zum Stand der Kausalanalyse mit Strukturgleichungsmodellen: Methodische Trends und Software-Entwicklungen," SFB 373 Discussion Papers 1999,46, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. Kalaitzandonakes, Nicholas G. & Dunn, Elizabeth G., 1995. "Technical Efficiency, Managerial Ability And Farmer Education In Guatemalan Corn Production: A Latent Variable Analysis," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 24(1), April.
    7. Ivaldi, Marc & Monier-Dilhan, Sylvette & Simioni, Michel, 1995. "Stochastic production frontiers and panel data: A latent variable framework," European Journal of Operational Research, Elsevier, vol. 80(3), pages 534-547, February.
    8. Albert Satorra, 1991. "Asymptotic robust inferences in the analysis of mean and covariance structures," Economics Working Papers 3, Department of Economics and Business, Universitat Pompeu Fabra.
    9. Yuan, Ke-Hai & Bentler, Peter M., 1997. "Improving parameter tests in covariance structure analysis," Computational Statistics & Data Analysis, Elsevier, vol. 26(2), pages 177-198, December.
    10. Tenko Raykov & Spiridon Penev, 1997. "Structural equation modeling and the latent linearity hypothesis in social and behavioral research," Quality & Quantity: International Journal of Methodology, Springer, vol. 31(1), pages 57-78, February.

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