Kevin J. Grimm
Statistics and Probability · with Ram · 2007–2010
A researcher in the Science corpus: 6 papers; trusts 31 researchers and is trusted by 21 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 21 citations into it
- Management Science and Operations Research — 18 citations into it; #6,985 of 11,946 by trust here, #7,262 by citations
- Artificial Intelligence — 14 citations into it
- Experimental and Cognitive Psychology — 11 citations into it; #2,584 of 9,731 by trust here, #6,373 by citations
- Education — 10 citations into it; #2,289 of 11,309 by trust here, #2,786 by citations
- Computer Networks and Communications — 9 citations into it
- Sociology and Political Science — 5 citations into it
Whom Kevin J. Grimm trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- J. Mcardle
- Kenneth A. Bollen
- Fumiaki Hamagami
- P. Curran
- Sehee Hong
- B. Muthén
- T. Little
- R. Cudeck
- Nilam Ram
- Stephen A. Sivo
Who trusts Kevin J. Grimm overall
- Karen Nylund-Gibson
- J. Mcardle
- Nilam Ram
- Nikos Ntoumanis
- Keith B Burt
- U. Orth
- K. Berlin
- G. Ladd
- Laura H. B. Dinehart
- Alexandre J. S. Morin
Papers from Kevin J. Grimm's perspective
Ordered by how strongly the researchers Kevin J. Grimm trusts endorse each paper. Same corpus, a different order for every researcher.
- The best of both worlds: Combining autoregressive and latent curve models.
- Applied Longitudinal Data Analysis
- Statistical Analysis With Missing Data
- Book Review : Structural Equations with Latent Variables Kenneth A. Bollen New York: Wiley, 1989, 514 pp., approx. $44.95
- Distributional assumptions of growth mixture models: implications for overextraction of latent trajectory classes. (Psychological methods)
- Statistical and substantive checking in growth mixture modeling: comment on Bauer and Curran (2003). (Psychological methods)
- Latent curve models: A structural equation perspective
- Group-Based Modeling of Development
- Latent Variable Analysis: Growth Mixture Modeling and Related Techniques for Longitudinal Data
- Autoregressive Latent Trajectory (ALT) Models A Synthesis of Two Traditions
Their papers
- Using simple and complex growth models to articulate developmental change: Matching theory to method (2007) — 298 citations
- Multivariate longitudinal methods for studying developmental relationships between depression and academic achievement (2007) — 125 citations
- Fine motor skills and early comprehension of the world: two new school readiness indicators. (2010) — 597 citations
- Residual Structures in Latent Growth Curve Modeling (2010) — 80 citations
- Five Steps in Latent Curve and Latent Change Score Modeling with Longitudinal Data (2010) — 109 citations
- Methods and Measures: Growth mixture modeling: A method for identifying differences in longitudinal change among unobserved groups (2009) — 1,081 citations