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Parametric functional principal component analysis.

Biometrics

Sang P, Wang L, Cao J.
PMID: 28295173
Biometrics. 2017 Sep;73(3):802-810. doi: 10.1111/biom.12641. Epub 2017 Mar 10.

Functional principal component analysis (FPCA) is a popular approach in functional data analysis to explore major sources of variation in a sample of random curves. These major sources of variation are represented by functional principal components (FPCs). Most existing...

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Sang P, Wang L, Cao J. Parametric functional principal component analysis. Biometrics. 2017;73(3):802-810doi: 10.1111/biom.12641.
Sang, P., Wang, L., & Cao, J. (2017). Parametric functional principal component analysis. Biometrics, 73(3), 802-810. https://doi.org/10.1111/biom.12641
Sang, Peijun, et al. "Parametric functional principal component analysis." Biometrics vol. 73,3 (2017): 802-810. doi: https://doi.org/10.1111/biom.12641
Sang P, Wang L, Cao J. Parametric functional principal component analysis. Biometrics. 2017 Sep;73(3):802-810. doi: 10.1111/biom.12641. Epub 2017 Mar 10. PMID: 28295173.
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Refining a socio-economic status scale for use in community-based health research in India.

Journal of postgraduate medicine

Dudeja P, Bahuguna P, Singh A, Bhatnagar N.
PMID: 25766337
J Postgrad Med. 2015 Apr-Jun;61(2):77-83. doi: 10.4103/0022-3859.150442.

OBJECTIVE: Socio economic status is an important determinant of health and disease in population. Various scales for measuring the same exist in modern Indian society each with it's own limitations. Present study was done to abridge the existing and...

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Dudeja P, Bahuguna P, Singh A, et al. Refining a socio-economic status scale for use in community-based health research in India. J Postgrad Med. 2015;61(2):77-83doi: 10.4103/0022-3859.150442.
Dudeja, P., Bahuguna, P., Singh, A., & Bhatnagar, N. (2015). Refining a socio-economic status scale for use in community-based health research in India. Journal of postgraduate medicine, 61(2), 77-83. https://doi.org/10.4103/0022-3859.150442
Dudeja, P, et al. "Refining a socio-economic status scale for use in community-based health research in India." Journal of postgraduate medicine vol. 61,2 (2015): 77-83. doi: https://doi.org/10.4103/0022-3859.150442
Dudeja P, Bahuguna P, Singh A, Bhatnagar N. Refining a socio-economic status scale for use in community-based health research in India. J Postgrad Med. 2015 Apr-Jun;61(2):77-83. doi: 10.4103/0022-3859.150442. PMID: 25766337; PMCID: PMC4943423.
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Relationship among practice change, motivation, and self-efficacy.

The Journal of continuing education in the health professions

Williams BW, Kessler HA, Williams MV.
PMID: 24935884
J Contin Educ Health Prof. 2014;34:S5-10. doi: 10.1002/chp.21235.

INTRODUCTION: The relationship between an individual's sense of self-efficacy, motivation to change, and the implementation of improvement programs has been reported. This research reports the relationship among self-efficacy, motivation to change, and intent to implement continuing medical education (CME)...

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Williams BW, Kessler HA, Williams MV. Relationship among practice change, motivation, and self-efficacy. J Contin Educ Health Prof. 2014;34:S5-10doi: 10.1002/chp.21235.
Williams, B. W., Kessler, H. A., & Williams, M. V. (2014). Relationship among practice change, motivation, and self-efficacy. The Journal of continuing education in the health professions, 34S5-10. https://doi.org/10.1002/chp.21235
Williams, Betsy W, et al. "Relationship among practice change, motivation, and self-efficacy." The Journal of continuing education in the health professions vol. 34 (2014): S5-10. doi: https://doi.org/10.1002/chp.21235
Williams BW, Kessler HA, Williams MV. Relationship among practice change, motivation, and self-efficacy. J Contin Educ Health Prof. 2014;34:S5-10. doi: 10.1002/chp.21235. PMID: 24935884.
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Drug-symptom networking: Linking drug-likeness screening to drug discovery.

Pharmacological research

Xu X, Zhang C, Li P, Zhang F, Gao K, Chen J, Shang H.
PMID: 26615785
Pharmacol Res. 2016 Jan;103:105-13. doi: 10.1016/j.phrs.2015.11.015. Epub 2015 Nov 23.

Understanding the relationships between drugs and symptoms has broad medical consequences, yet a comprehensive description of the drug-symptom associations is currently lacking. Here, 1441 FDA-approved drugs were collected, and PCA was used to extract 122 descriptors which explained 91%...

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Xu X, Zhang C, Li P, et al. Drug-symptom networking: Linking drug-likeness screening to drug discovery. Pharmacol Res. 2015;103:105-13doi: 10.1016/j.phrs.2015.11.015.
Xu, X., Zhang, C., Li, P., Zhang, F., Gao, K., Chen, J., & Shang, H. (2016). Drug-symptom networking: Linking drug-likeness screening to drug discovery. Pharmacological research, 103105-13. https://doi.org/10.1016/j.phrs.2015.11.015
Xu, Xue, et al. "Drug-symptom networking: Linking drug-likeness screening to drug discovery." Pharmacological research vol. 103 (2016): 105-13. doi: https://doi.org/10.1016/j.phrs.2015.11.015
Xu X, Zhang C, Li P, Zhang F, Gao K, Chen J, Shang H. Drug-symptom networking: Linking drug-likeness screening to drug discovery. Pharmacol Res. 2016 Jan;103:105-13. doi: 10.1016/j.phrs.2015.11.015. Epub 2015 Nov 23. PMID: 26615785.
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Applying stability selection to consistently estimate sparse principal components in high-dimensional molecular data.

Bioinformatics (Oxford, England)

Sill M, Saadati M, Benner A.
PMID: 25861969
Bioinformatics. 2015 Aug 15;31(16):2683-90. doi: 10.1093/bioinformatics/btv197. Epub 2015 Apr 10.

MOTIVATION: Principal component analysis (PCA) is a basic tool often used in bioinformatics for visualization and dimension reduction. However, it is known that PCA may not consistently estimate the true direction of maximal variability in high-dimensional, low sample size...

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Sill M, Saadati M, Benner A. Applying stability selection to consistently estimate sparse principal components in high-dimensional molecular data. Bioinformatics. 2015;31(16):2683-90doi: 10.1093/bioinformatics/btv197.
Sill, M., Saadati, M., & Benner, A. (2015). Applying stability selection to consistently estimate sparse principal components in high-dimensional molecular data. Bioinformatics (Oxford, England), 31(16), 2683-90. https://doi.org/10.1093/bioinformatics/btv197
Sill, Martin, et al. "Applying stability selection to consistently estimate sparse principal components in high-dimensional molecular data." Bioinformatics (Oxford, England) vol. 31,16 (2015): 2683-90. doi: https://doi.org/10.1093/bioinformatics/btv197
Sill M, Saadati M, Benner A. Applying stability selection to consistently estimate sparse principal components in high-dimensional molecular data. Bioinformatics. 2015 Aug 15;31(16):2683-90. doi: 10.1093/bioinformatics/btv197. Epub 2015 Apr 10. PMID: 25861969; PMCID: PMC4528629.
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Comparative evaluation of eight software programs for alignment of gas chromatography-mass spectrometry chromatograms in metabolomics experiments.

Journal of chromatography. A

Niu W, Knight E, Xia Q, McGarvey BD.
PMID: 25435458
J Chromatogr A. 2014 Dec 29;1374:199-206. doi: 10.1016/j.chroma.2014.11.005. Epub 2014 Nov 20.

Since retention times of compounds in GC-MS chromatograms always vary slightly from chromatogram to chromatogram, it is necessary to align chromatograms before comparing them in metabolomics experiments. Several software programs have been developed to automate this process. Here we...

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Niu W, Knight E, Xia Q, et al. Comparative evaluation of eight software programs for alignment of gas chromatography-mass spectrometry chromatograms in metabolomics experiments. J Chromatogr A. 2014;1374:199-206doi: 10.1016/j.chroma.2014.11.005.
Niu, W., Knight, E., Xia, Q., & McGarvey, B. D. (2014). Comparative evaluation of eight software programs for alignment of gas chromatography-mass spectrometry chromatograms in metabolomics experiments. Journal of chromatography. A, 1374199-206. https://doi.org/10.1016/j.chroma.2014.11.005
Niu, Weihuan, et al. "Comparative evaluation of eight software programs for alignment of gas chromatography-mass spectrometry chromatograms in metabolomics experiments." Journal of chromatography. A vol. 1374 (2014): 199-206. doi: https://doi.org/10.1016/j.chroma.2014.11.005
Niu W, Knight E, Xia Q, McGarvey BD. Comparative evaluation of eight software programs for alignment of gas chromatography-mass spectrometry chromatograms in metabolomics experiments. J Chromatogr A. 2014 Dec 29;1374:199-206. doi: 10.1016/j.chroma.2014.11.005. Epub 2014 Nov 20. PMID: 25435458.
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Development and Validation of a Short Version of the Supervisory Relationship Questionnaire.

Clinical psychology & psychotherapy

Cliffe T, Beinart H, Cooper M.
PMID: 25504780
Clin Psychol Psychother. 2016 Jan-Feb;23(1):77-86. doi: 10.1002/cpp.1935. Epub 2014 Dec 11.

UNLABELLED: The Supervisory Relationship Questionnaire (SRQ) is one of the few theoretically sound and psychometrically valid questionnaires for measuring the SR within clinical supervision. However, its length can make it difficult to use in clinical practice and research. This...

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Cliffe T, Beinart H, Cooper M. Development and Validation of a Short Version of the Supervisory Relationship Questionnaire. Clin Psychol Psychother. 2014;23(1):77-86doi: 10.1002/cpp.1935.
Cliffe, T., Beinart, H., & Cooper, M. (2016). Development and Validation of a Short Version of the Supervisory Relationship Questionnaire. Clinical psychology & psychotherapy, 23(1), 77-86. https://doi.org/10.1002/cpp.1935
Cliffe, Tom, et al. "Development and Validation of a Short Version of the Supervisory Relationship Questionnaire." Clinical psychology & psychotherapy vol. 23,1 (2016): 77-86. doi: https://doi.org/10.1002/cpp.1935
Cliffe T, Beinart H, Cooper M. Development and Validation of a Short Version of the Supervisory Relationship Questionnaire. Clin Psychol Psychother. 2016 Jan-Feb;23(1):77-86. doi: 10.1002/cpp.1935. Epub 2014 Dec 11. PMID: 25504780.
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The making of meaning: comments on Hofstee and Ten Berge.

Journal of personality assessment

McGrath RE.
PMID: 15456647
J Pers Assess. 2004 Oct;83(2):128-30; discussion 136-40. doi: 10.1207/s15327752jpa8302_05.

Hofstee and Ten Berge (2004/this issue) outline a method of scale transformation that places scores on a common absolute scale. This contrasts with traditional relative methods of transformation, which involve scaling in relation to a sample mean. Their primary...

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McGrath RE. The making of meaning: comments on Hofstee and Ten Berge. J Pers Assess. 2004;83(2):128-30; discussion 136-40doi: 10.1207/s15327752jpa8302_05.
McGrath, R. E. (2004). The making of meaning: comments on Hofstee and Ten Berge. Journal of personality assessment, 83(2), 128-30; discussion 136-40. https://doi.org/10.1207/s15327752jpa8302_05
McGrath, Robert E. "The making of meaning: comments on Hofstee and Ten Berge." Journal of personality assessment vol. 83,2 (2004): 128-30; discussion 136-40. doi: https://doi.org/10.1207/s15327752jpa8302_05
McGrath RE. The making of meaning: comments on Hofstee and Ten Berge. J Pers Assess. 2004 Oct;83(2):128-30; discussion 136-40. doi: 10.1207/s15327752jpa8302_05. PMID: 15456647.
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Constructing socio-economic status indices: how to use principal components analysis.

Health policy and planning

Vyas S, Kumaranayake L.
PMID: 17030551
Health Policy Plan. 2006 Nov;21(6):459-68. doi: 10.1093/heapol/czl029. Epub 2006 Oct 09.

Theoretically, measures of household wealth can be reflected by income, consumption or expenditure information. However, the collection of accurate income and consumption data requires extensive resources for household surveys. Given the increasingly routine application of principal components analysis (PCA)...

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Vyas S, Kumaranayake L. Constructing socio-economic status indices: how to use principal components analysis. Health Policy Plan. 2006;21(6):459-68doi: 10.1093/heapol/czl029.
Vyas, S., & Kumaranayake, L. (2006). Constructing socio-economic status indices: how to use principal components analysis. Health policy and planning, 21(6), 459-68. https://doi.org/10.1093/heapol/czl029
Vyas, Seema, and Kumaranayake, Lilani. "Constructing socio-economic status indices: how to use principal components analysis." Health policy and planning vol. 21,6 (2006): 459-68. doi: https://doi.org/10.1093/heapol/czl029
Vyas S, Kumaranayake L. Constructing socio-economic status indices: how to use principal components analysis. Health Policy Plan. 2006 Nov;21(6):459-68. doi: 10.1093/heapol/czl029. Epub 2006 Oct 09. PMID: 17030551.
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Mapping co-variates of mortality up to age of five years for Indian states.

Indian journal of public health

Bhagavandas M, Josha V.
PMID: 14723291
Indian J Public Health. 2003 Jan-Mar;47(1):22-6.

The study was conducted to obtain an index and a map with natural clusters by simultaneously considering sereral covariates of mortality and its indicators upto the age of five years for Indian states, Survey reports on various co-variates of...

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Bhagavandas M, Josha V. Mapping co-variates of mortality up to age of five years for Indian states. Indian J Public Health. 2003;47(1):22-6
Bhagavandas, M., & Josha, V. (2003). Mapping co-variates of mortality up to age of five years for Indian states. Indian journal of public health, 47(1), 22-6.
Bhagavandas, M, and Josha, V. "Mapping co-variates of mortality up to age of five years for Indian states." Indian journal of public health vol. 47,1 (2003): 22-6.
Bhagavandas M, Josha V. Mapping co-variates of mortality up to age of five years for Indian states. Indian J Public Health. 2003 Jan-Mar;47(1):22-6. PMID: 14723291.
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[Evaluation of germplasm resource of Ophiopogon japonicus in Sichuan basin based on principal component and cluster analysis].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica

Liu J, Chen X, Liu S, Yang W, Du G, Liu W.
PMID: 20506813
Zhongguo Zhong Yao Za Zhi. 2010 Mar;35(5):569-73. doi: 10.4268/cjcmm20100506.

OBJECTIVE: To compare and appraise the quality of germplasm resource of Ophiopogon japonicus in Sichuan basin.METHOD: According to the main contents and yield traits, 24 wild germplasm resources of O. japonicus from different areas of Sichuan basin were comprehensively...

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Liu J, Chen X, Liu S, et al. [Evaluation of germplasm resource of Ophiopogon japonicus in Sichuan basin based on principal component and cluster analysis]. Zhongguo Zhong Yao Za Zhi. 2010;35(5):569-73doi: 10.4268/cjcmm20100506.
Liu, J., Chen, X., Liu, S., Yang, W., Du, G., & Liu, W. (2010). [Evaluation of germplasm resource of Ophiopogon japonicus in Sichuan basin based on principal component and cluster analysis]. Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica, 35(5), 569-73. https://doi.org/10.4268/cjcmm20100506
Liu, Jiang, et al. "[Evaluation of germplasm resource of Ophiopogon japonicus in Sichuan basin based on principal component and cluster analysis]." Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica vol. 35,5 (2010): 569-73. doi: https://doi.org/10.4268/cjcmm20100506
Liu J, Chen X, Liu S, Yang W, Du G, Liu W. [Evaluation of germplasm resource of Ophiopogon japonicus in Sichuan basin based on principal component and cluster analysis]. Zhongguo Zhong Yao Za Zhi. 2010 Mar;35(5):569-73. doi: 10.4268/cjcmm20100506. Chinese. PMID: 20506813.
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Coupled principal component analysis.

IEEE transactions on neural networks

Möller R, Könies A.
PMID: 15387263
IEEE Trans Neural Netw. 2004 Jan;15(1):214-22. doi: 10.1109/TNN.2003.820439.

A framework for a class of coupled principal component learning rules is presented. In coupled rules, eigenvectors and eigenvalues of a covariance matrix are simultaneously estimated in coupled equations. Coupled rules can mitigate the stability-speed problem affecting noncoupled learning...

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Möller R, Könies A. Coupled principal component analysis. IEEE Trans Neural Netw. 2004;15(1):214-22doi: 10.1109/TNN.2003.820439.
Möller, R., & Könies, A. (2004). Coupled principal component analysis. IEEE transactions on neural networks, 15(1), 214-22. https://doi.org/10.1109/TNN.2003.820439
Möller, Ralf, and Könies, Axel. "Coupled principal component analysis." IEEE transactions on neural networks vol. 15,1 (2004): 214-22. doi: https://doi.org/10.1109/TNN.2003.820439
Möller R, Könies A. Coupled principal component analysis. IEEE Trans Neural Netw. 2004 Jan;15(1):214-22. doi: 10.1109/TNN.2003.820439. PMID: 15387263.
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Showing 1 to 12 of 110 entries