The development of summary components for the Disablement in the Physically Active scale in collegiate athletes
29
Citation
12
Reference
10
Related Paper
Citation Trend
The article discusses selected problems related to both principal component analysis (PCA) and factor analysis (FA). In particular, both types of analysis were compared. A vector interpretation for both PCA and FA has also been proposed. The problem of determining the number of principal components in PCA and factors in FA was discussed in detail. A new criterion for determining the number of factors and principal components is discussed, which will allow to present most of the variance of each of the analyzed primary variables. An efficient algorithm for determining the number of factors in FA, which complies with this criterion, was also proposed. This algorithm was adapted to find the number of principal components in PCA. It was also proposed to modify the PCA algorithm using a new method of determining the number of principal components. The obtained results were discussed.
Sparse PCA
Factor Analysis
Cite
Citations (0)
Component analysis
Sparse PCA
Factor Analysis
Rank (graph theory)
Factor (programming language)
Component (thermodynamics)
Cite
Citations (1)
The significant amount of variance in head-related transfer functions (HRTFs) resulting from source location and subject dependencies have led researchers to use principal components analysis (PCA) to approximate HRTFs with a small set of basis functions. PCA minimizes a mean-square error, and consequently may spend modeling effort on perceptually irrelevant properties. To investigate the extent of this effect, PCA performance was studied before and after removal of perceptually irrelevant variance. The results indicate that from the sixth PCA component onward, a substantial amount of perceptually irrelevant variance is being accounted for.
Explained variation
Variance components
Cite
Citations (5)
Psychosocial Support
Cite
Citations (9)
ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTClassification of Vegetable Oils by Principal Component Analysis of FTIR SpectraDavid A. Rusak , Leah M. Brown , and Scott D. Martin View Author Information Department of Chemistry, University of Scranton, Scranton, PA 18510Cite this: J. Chem. Educ. 2003, 80, 5, 541Publication Date (Web):May 1, 2003Publication History Received3 August 2009Published online1 May 2003Published inissue 1 May 2003https://pubs.acs.org/doi/10.1021/ed080p541https://doi.org/10.1021/ed080p541research-articleACS PublicationsRequest reuse permissionsArticle Views2531Altmetric-Citations42LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Infrared light,Lipids,Mathematical methods,Plant derived food,Principal component analysis Get e-Alerts
Chemometrics
Plot (graphics)
Cite
Citations (53)
The study explores the psychosocial care-givers knowledge and skills on medical and psychosocial issues in Hemophilia pre-and post participation in the training program conducted in four different North Indian States. The objectives of the study is 1) To approach a cross-section of psychosocial workers and ascertain their views on the psychosocial support in Hemophilia; 2) To critically examine the views/perceptions of the psychosocial workers pre and post training workshop .3) To analyze the responses of the psychosocial workers about medical and psychosocial implications of hemophilia. 4) To identify issues, emerging from empirical evidence, which could be utilized for preparing the guidelines for the psychosocial workers. The findings showed that overall the psychosocial care-givers awareness improved post training on different subsets on the psychosocial awareness questionnaire. This indicates that regular education and updating of knowledge of the care-givers is important. A close perusal of findings suggests that age and experience were closely related to the awareness on the psychosocial issues in Hemophilia. It was found that the young respondents' awareness significantly improved post training whereas there were moderate changes in the responses of the older participants. On the whole, the change in awareness level witnessed after training illustrates that by providing adequate education and information, good results can be achieved, that will benefit PWH and their families, as well as those responsible for giving care to patients suffering from hemophilia.
Cite
Citations (0)
Cite
Citations (3)
Cite
Citations (1)
Principal component analysis (PCA) has been widely used for data dimension reduction and process fault detection. However, interpreting the principal components and the outcomes of PCA-based monitoring techniques is a challenging task since each principal component is a linear combination of the original variables which can be numerous in most modern applications. To address this challenge, we first propose the use of sparse principal component analysis (SPCA) where the loadings of some variables in principal components are restricted to zero. This paper then describes a technique to determine the number of non-zero loadings in each principal component. Furthermore, we compare the performance of PCA and SPCA in fault detection. The validity and potential of SPCA are demonstrated through simulated data and a comparative study with the benchmark Tennessee Eastman process.
Sparse PCA
Benchmark (surveying)
Cite
Citations (13)