Dataset Information

On the similarity between exchangeable profiles: A psychometric model, analytic strategy, and empirical illustration.

ABSTRACT: Analyses of profile similarity are widespread in personality psychology, but their apparent simplicity masks difficult psychometric and statistical issues. We present a psychometric framework that addresses an important challenge (i.e., profile normativeness) in examinations of dyadic exchangeable profiles. In addition, we present an analytic strategy accounting for non-independence that often arises in analyses of profile similarity, facilitating integrated examinations of variables at dyadic and individual levels. An empirical analysis of personality similarity and relationship quality demonstrates that the model and analytic strategy can reveal novel psychological insights. These are important advances, as previous work has ignored exchangeable profiles and has failed to present an integrated psychometric and statistical framework for profile similarity.

SUBMITTER: Furr RM

PROVIDER: S-EPMC3771326 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

On the similarity between exchangeable profiles: A psychometric model, analytic strategy, and empirical illustration.

Furr R Michael RM Wood Dustin D

Journal of research in personality 20130601 3

Analyses of profile similarity are widespread in personality psychology, but their apparent simplicity masks difficult psychometric and statistical issues. We present a psychometric framework that addresses an important challenge (i.e., profile normativeness) in examinations of dyadic exchangeable profiles. In addition, we present an analytic strategy accounting for non-independence that often arises in analyses of profile similarity, facilitating integrated examinations of variables at dyadic a ...[more]

PMID: 24039314

Similar Datasets

Project description:BackgroundRobust transcriptional signatures in cancer can be identified by data similarity-driven meta-analysis of gene expression profiles. An unbiased data integration and interrogation strategy has not previously been available.Methods and findingsWe implemented and performed a large meta-analysis of breast cancer gene expression profiles from 223 datasets containing 10,581 human breast cancer samples using a novel data similarity-based approach (iterative EXALT). Cancer gene expression signatures extracted from individual datasets were clustered by data similarity and consolidated into a meta-signature with a recurrent and concordant gene expression pattern. A retrospective survival analysis was performed to evaluate the predictive power of a novel meta-signature deduced from transcriptional profiling studies of human breast cancer. Validation cohorts consisting of 6,011 breast cancer patients from 21 different breast cancer datasets and 1,110 patients with other malignancies (lung and prostate cancer) were used to test the robustness of our findings. During the iterative EXALT analysis, 633 signatures were grouped by their data similarity and formed 121 signature clusters. From the 121 signature clusters, we identified a unique meta-signature (BRmet50) based on a cluster of 11 signatures sharing a phenotype related to highly aggressive breast cancer. In patients with breast cancer, there was a significant association between BRmet50 and disease outcome, and the prognostic power of BRmet50 was independent of common clinical and pathologic covariates. Furthermore, the prognostic value of BRmet50 was not specific to breast cancer, as it also predicted survival in prostate and lung cancers.ConclusionsWe have established and implemented a novel data similarity-driven meta-analysis strategy. Using this approach, we identified a transcriptional meta-signature (BRmet50) in breast cancer, and the prognostic performance of BRmet50 was robust and applicable across a wide range of cancer-patient populations.

Dataset Information

On the similarity between exchangeable profiles: A psychometric model, analytic strategy, and empirical illustration.

Publications

On the similarity between exchangeable profiles: A psychometric model, analytic strategy, and empirical illustration.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets