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Journal ArticleDOI

Identification of separable cognitive factors in schizophrenia.

TLDR
Empirical evidence for cognitive performance dimensions in schizophrenia was evaluated and seven separable cognitive factors were replicable across studies and represent fundamental dimensions of cognitive deficit in schizophrenia: Speed of Processing, Attention/Vigilance, Working Memory, Verbal Learning and Memory, Visual Learning and memory, Reasoning and Problem Solving, and Verbal Comprehension.
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This article is published in Schizophrenia Research.The article was published on 2004-12-15. It has received 1215 citations till now. The article focuses on the topics: Cognitive neuropsychology & Cognitive remediation therapy.

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Citations
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The relationship between neurocognition and social cognition with functional outcomes in schizophrenia: a meta-analysis.

TL;DR: Overall, social cognition was more strongly associated with community functioning than neurocognition, with the strongest associations being between theory of mind and functional outcomes.
Journal ArticleDOI

A meta-analysis of cognitive remediation in schizophrenia

TL;DR: Cognitive remediation produces moderate improvements in cognitive performance and, when combined with psychiatric rehabilitation, also improves functional outcomes.
Journal ArticleDOI

Neurocognition in First-Episode Schizophrenia: A Meta-Analytic Review

TL;DR: A meta-analysis of neurocognitive findings from 47 studies of first-episode schizophrenia published through October 2007 indicates that impairments are reliably and broadly present by the FE, approach or match the degree of deficit shown in well-established illness, and are maximal in immediate verbal memory and processing speed.
References
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Book

Principal Component Analysis

TL;DR: In this article, the authors present a graphical representation of data using Principal Component Analysis (PCA) for time series and other non-independent data, as well as a generalization and adaptation of principal component analysis.
Book

Testing Structural Equation Models

TL;DR: In this paper, Bollen et al. proposed a model fitting metric for Structural Equation Models, which is based on the Monte Carlo evaluation of Goodness-of-Fit measures.
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