Tony Jung

Statistics and Probability · 2008

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

Whom Tony Jung trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. B. Muthén
  2. Daniel J. Bauer
  3. R. Maccallum
  4. P. Curran
  5. Yungtai Lo
  6. B. Jones
  7. K. Nylund
  8. T. Asparouhov
  9. Dan Nagin
  10. L. A. Goodman

Who trusts Tony Jung overall

  1. A. Masten
  2. Alex J. Bowers
  3. G. Bonanno
  4. Paul J Silvia
  5. Angela Urick
  6. Katherine W. Paschall
  7. S. Anderson
  8. Sheila B. Frankfurt
  9. R. Sprott
  10. T. Kashdan

Papers from Tony Jung's perspective

Ordered by how strongly the researchers Tony Jung trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Testing the number of components in a normal mixture
  2. Latent Variable Analysis: Growth Mixture Modeling and Related Techniques for Longitudinal Data
  3. Statistical and substantive checking in growth mixture modeling: comment on Bauer and Curran (2003). (Psychological methods)
  4. Distributional assumptions of growth mixture models: implications for overextraction of latent trajectory classes. (Psychological methods)
  5. A SAS Procedure Based on Mixture Models for Estimating Developmental Trajectories
  6. Integrating person-centered and variable-centered analyses: growth mixture modeling with latent trajectory classes. (Alcoholism: Clinical and Experimental Research)
  7. Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study
  8. Local solutions in the estimation of growth mixture models. (Psychological methods)
  9. Overextraction of latent trajectory classes: Much ado about nothing? Reply to Rindskopf (2003), Muthén (2003), and Cudeck and Henly (2003)
  10. Book Review : Structural Equations with Latent Variables Kenneth A. Bollen New York: Wiley, 1989, 514 pp., approx. $44.95

Their papers