Jeffrey D. Long
Statistics and Probability · 2001–2014
A researcher in the Science corpus: 10 papers; trusts 16 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 47 citations into it; #8,204 of 12,932 by trust here, #5,661 by citations
- Developmental and Educational Psychology — 34 citations into it; #6,702 of 8,223 by trust here, #7,501 by citations
- Clinical Psychology — 19 citations into it; #1,379 of 8,024 by trust here, #753 by citations
- Experimental and Cognitive Psychology — 15 citations into it; #6,756 of 9,731 by trust here, #7,398 by citations
- Artificial Intelligence — 12 citations into it
- Social Psychology — 10 citations into it; #3,403 of 15,694 by trust here, #2,699 by citations
- Cognitive Neuroscience — 8 citations into it
- Management Science and Operations Research — 6 citations into it
Whom Jeffrey D. Long trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Craig K. Enders
- J. Graham
- Anthony D. Pellegrini
- Joseph L. Schafer
- Peter M. Bentler
- M. Bartini
- Michael S. Gold
- Peter K. Smith
- Ke-Hai Yuan
- Victoria Savalei
Who trusts Jeffrey D. Long overall
- A. Masten
- Rebecca J. Collie
- V. P. Poteat
- Dorothy Espelage
- Rachel R. Harari
- Anthony D. Pellegrini
- Christina Salmivalli
- Joey T. Cheng
- A. Schulte
Papers from Jeffrey D. Long's perspective
Ordered by how strongly the researchers Jeffrey D. Long trusts endorse each paper. Same corpus, a different order for every researcher.
- Missing data: our view of the state of the art. (Psychological methods)
- Statistical Analysis with Missing Data: Little/Statistical Analysis with Missing Data
- Adding Missing-Data-Relevant Variables to FIML-Based Structural Equation Models
- The Relative Performance of Full Information Maximum Likelihood Estimation for Missing Data in Structural Equation Models
- The impact of nonnormality on full information maximum-likelihood estimation for structural equation models with missing data. (Psychological methods)
- Modeling longitudinal and multilevel data: Practical issues, applied approaches, and specific examples.
- A comparison of inclusive and restrictive strategies in modern missing data procedures. (Psychological methods)
- Linear Mixed Models for Longitudinal Data (Technometrics)
- Treatments of Missing Data: A Monte Carlo Comparison of RBHDI, Iterative Stochastic Regression Imputation, and Expectation-Maximization
- The Two Sexes: Growing Up Apart: Coming Together
Their papers
- A longitudinal study of bullying, dominance, and victimization during the transition from primary school through secondary school (2002) — 1,052 citations
- Developmental changes in hypothalamus–pituitary–adrenal activity over the transition to adolescence: Normative changes and associations with puberty (2009) — 639 citations
- A Confirmatory Factor Analysis of the Mathematics Anxiety Scale for Children (2001) — 47 citations
- Huntington disease: natural history, biomarkers and prospects for therapeutics (2014) — 967 citations
- Exploring gains in reading and mathematics achievement among regular and exceptional students using (2013) — 96 citations
- Executive Function Skills and School Success in Young Children Experiencing Homelessness (2012) — 207 citations
- Creating a Progress–Monitoring System in Reading for Middle–School Students: Tracking Progress toward Meeting High–Stakes Standards (2010) — 97 citations
- Effects of Missing Data Methods in Structural Equation Modeling With Nonnormal Longitudinal Data (2009) — 81 citations
- Developmental cascades: linking academic achievement and externalizing and internalizing symptoms over 20 years. (2005) — 1,167 citations
- Ordinal Analysis of Behavioral Data (2003) — 60 citations