Relaxation mode analysis of a peptide system: Comparison with principal component analysis

2011 ◽  
Vol 135 (16) ◽  
pp. 164102 ◽  
Author(s):  
Ayori Mitsutake ◽  
Hiromitsu Iijima ◽  
Hiroshi Takano
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Mode Analysis ◽  
Relaxation Mode ◽  
Peptide System

Principal Component Analysis Of Three -Way Data

1994 ◽  
Author(s):  
Michael Edward Hohn
Keyword(s):  
Principal Component Analysis ◽  
Three Dimensional ◽  
Principal Component ◽  
Component Analysis ◽  
Quality Data ◽  
Mode Analysis ◽  
Core Matrix ◽  
Eigenvector Analysis ◽  
Different Depths ◽  
Principal Component Model

Extension of conventional eigenvector analysis to three-way sets of data is possible through three-mode principal component analysis. First introduced in the 1960's, this method gives three sets of loadings corresponding to the three ways in the data, e.g., variable, location, and time. A core matrix relates loadings across modes. Data must be centered and scaled before analysis, and as in conventional two-way analysis, preprocessing options affect the reduction in dimensionality and the appearance of the results. An example using water quality data illustrates the method and preprocessing effects. Although three-way tables can be studied through conventional analysis of a two-way table created by combining two modes of the data, three-mode analysis treats each mode separately and with the same weight. In addition, a restricted three-mode principal component model avoids problems in rotational indeterminacy, and results in a particularly simple model. Factor analysis or principal component analysis begins with a two-way table with samples along one margin and variables along the other. For instance, samples may be arranged as rows and variables as columns. R-mode analysis of the columns displays interdependencies among variables and Q-mode analysis displays similarities among samples. The analysis increases in complexity if a set of variables is repeatedly observed on the same samples; each set of measurements might represent a different experimental condition, chemical or sedimentological fraction, or simply geologic time. The resulting table of data can be visualized as a three-dimensional block: horizontal slices represent samples, vertical slices parallel with the front represent variables, and vertical slices parallel with the ends represent different conditions, times, or fractions. For example, Oudin (1970) performed elemental analyses of organic extracts from Jurassic shales in the Paris basin. Samples represented very different depths of maximum burial. Each was fractionated into several extracts according to solubility in organic solvents. Data published by Oudin (1970) have the three ways: locality, fraction, and element. Multivariate analysis of these data was presented by Hohn (1979). Hohn and Friberg (1979) applied principal component analysis to petrographic data in which the three modes were sample, mineral phase, and chemical component.

A German version of the Intermittent Claudication Questionnaire (ICQ): cultural adaptation and validation

VASA ◽  
2012 ◽  
Vol 41 (5) ◽  
pp. 333-342 ◽  
Author(s):  
Kirchberger ◽  
Finger ◽  
Müller-Bühl
Keyword(s):  
Principal Component Analysis ◽  
Intermittent Claudication ◽  
Completion Time ◽  
Short Form ◽  
Principal Component ◽  
Component Analysis ◽  
German Version ◽  
Average Completion Time ◽  
Sf 36 ◽  
Related Quality

Background: The Intermittent Claudication Questionnaire (ICQ) is a short questionnaire for the assessment of health-related quality of life (HRQOL) in patients with intermittent claudication (IC). The objective of this study was to translate the ICQ into German and to investigate the psychometric properties of the German ICQ version in patients with IC. Patients and methods: The original English version was translated using a forward-backward method. The resulting German version was reviewed by the author of the original version and an experienced clinician. Finally, it was tested for clarity with 5 German patients with IC. A sample of 81 patients were administered the German ICQ. The sample consisted of 58.0 % male patients with a median age of 71 years and a median IC duration of 36 months. Test of feasibility included completeness of questionnaires, completion time, and ratings of clarity, length and relevance. Reliability was assessed through a retest in 13 patients at 14 days, and analysis of Cronbach’s alpha for internal consistency. Construct validity was investigated using principal component analysis. Concurrent validity was assessed by correlating the ICQ scores with the Short Form 36 Health Survey (SF-36) as well as clinical measures. Results: The ICQ was completely filled in by 73 subjects (90.1 %) with an average completion time of 6.3 minutes. Cronbach’s alpha coefficient reached 0.75. Intra-class correlation for test-retest reliability was r = 0.88. Principal component analysis resulted in a 3 factor solution. The first factor explained 51.5 of the total variation and all items had loadings of at least 0.65 on it. The ICQ was significantly associated with the SF-36 and treadmill-walking distances whereas no association was found for resting ABPI. Conclusions: The German version of the ICQ demonstrated good feasibility, satisfactory reliability and good validity. Responsiveness should be investigated in further validation studies.

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