Eiko I. Fried

Experimental and Cognitive Psychology · 2014–2021

A researcher in the Science corpus: 13 papers; trusts 98 researchers and is trusted by 28 researchers here, as inferred from the citation graph.

Subfields

• Experimental and Cognitive Psychology — 200 citations into it; #477 of 9,731 by trust here, #974 by citations
• Cognitive Neuroscience — 108 citations into it; #893 of 10,852 by trust here, #1,972 by citations
• Clinical Psychology — 100 citations into it; #3,047 of 8,024 by trust here, #2,163 by citations
• Social Psychology — 77 citations into it
• Statistical and Nonlinear Physics — 60 citations into it; #1,156 of 10,127 by trust here, #2,849 by citations
• Statistics and Probability — 52 citations into it; #9,471 of 12,932 by trust here, #9,714 by citations
• Artificial Intelligence — 36 citations into it
• Applied Psychology — 35 citations into it

Whom Eiko I. Fried trusts overall

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

1. Denny Borsboom
2. Sacha Epskamp
3. A. Cramer
4. Robert Tibshirani
5. Peter C. M. Molenaar
6. Ronald C. Kessler
7. Helmut Ltkepohl
8. Lourens J. Waldorp
9. Yves Rosseel
10. G. Costantini

Who trusts Eiko I. Fried overall

1. Sacha Epskamp
2. D. Hevey
3. Jonas Everaert
4. Olivia Guest
5. Faidra Papanikolaou
6. A. Cramer
7. Jutta Joormann
8. G. Costantini
9. Denny Borsboom
10. Hudson F. Golino

Papers from Eiko I. Fried's perspective

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

1. Regression Shrinkage and Selection via the Lasso
2. High-dimensional graphs and variable selection with the Lasso
3. The Adaptive Lasso and Its Oracle Properties
4. The Elements of Statistical Learning
5. Estimating the Dimension of a Model
6. State of the aRt personality research: A tutorial on network analysis of personality data in R
7. Comorbidity: A network perspective (Behavioral and Brain Sciences)
8. Collective dynamics of ‘small-world’ networks
9. Social Network Analysis: Methods and Applications
10. Regularization Paths for Generalized Linear Models via Coordinate Descent

Their papers

• Measurement Schmeasurement: Questionable Measurement Practices and How to Avoid Them (2020) — 635 citations
• Network analysis of multivariate data in psychological science (2021) — 1,105 citations
• Mental Health and Social Contact During the COVID-19 Pandemic: An Ecological Momentary Assessment Study (2020) — 155 citations
• Lack of Theory Building and Testing Impedes Progress in The Factor and Network Literature (2020) — 239 citations
• Moving Forward: Challenges and Directions for Psychopathological Network Theory and Methodology (2017) — 829 citations
• Mental disorders as networks of problems: a review of recent insights (2016) — 893 citations
• Estimating psychological networks and their accuracy: A tutorial paper (2016) — 4,610 citations
• What are 'good' depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis. (2016) — 637 citations
• Network Analysis of Depression and Anxiety Symptom Relations in a Psychiatric Sample (2016) — 738 citations
• A Tutorial on Regularized Partial Correlation Networks (2016) — 2,425 citations
• Development of Indirect Measures of Conscientiousness: Combining a Facets Approach and Network Analysis (2015) — 124 citations
• Depression sum-scores don’t add up: why analyzing specific depression symptoms is essential (2015) — 843 citations
• Depression is not a consistent syndrome: an investigation of unique symptom patterns in the STAR*D study (2014) — 900 citations