PCB primitive components analysis with TAN

2020 ◽  
pp. 55-76
Author(s):  
Zhifei Xu ◽  
Blaise Ravelo ◽  
Yang Liu ◽  
Olivier Maurice
Keyword(s):  
Components Analysis

Cluster analysis for large data sets: applications to individual aerosol particles from the mid-pacific

1992 ◽  
Vol 50 (2) ◽  
pp. 1488-1489
Author(s):  
Thomas W. Shattuck ◽  
James R. Anderson ◽  
Neil W. Tindale ◽  
Peter R. Buseck
Keyword(s):  
Cluster Analysis ◽  
Chemical Reactivity ◽  
Large Data ◽  
Large Data Sets ◽  
Particle Analysis ◽  
Data Sets ◽  
Halogen Chemistry ◽  
Complete Study ◽  
Components Analysis ◽  
Automated Scanning

Individual particle analysis involves the study of tens of thousands of particles using automated scanning electron microscopy and elemental analysis by energy-dispersive, x-ray emission spectroscopy (EDS). EDS produces large data sets that must be analyzed using multi-variate statistical techniques. A complete study uses cluster analysis, discriminant analysis, and factor or principal components analysis (PCA). The three techniques are used in the study of particles sampled during the FeLine cruise to the mid-Pacific ocean in the summer of 1990. The mid-Pacific aerosol provides information on long range particle transport, iron deposition, sea salt ageing, and halogen chemistry.Aerosol particle data sets suffer from a number of difficulties for pattern recognition using cluster analysis. There is a great disparity in the number of observations per cluster and the range of the variables in each cluster. The variables are not normally distributed, they are subject to considerable experimental error, and many values are zero, because of finite detection limits. Many of the clusters show considerable overlap, because of natural variability, agglomeration, and chemical reactivity.

Visual Evoked-Response Correlates of Speechreading Performance in Normal-Hearing Adults

1983 ◽  
Vol 26 (1) ◽  
pp. 2-9 ◽  
Author(s):  
Vincent J. Samar ◽  
Donald G. Sims
Keyword(s):  
Multiple Correlation Coefficient ◽  
Evoked Response ◽  
Multiple Correlation ◽  
Potential Significance ◽  
Visual Evoked Response ◽  
Latency Measure ◽  
Two Measures ◽  
Components Analysis ◽  
The Relationship ◽  
Visual Evoked

The relationship between the latency of the negative peak occurring at approximately 130 msec in the visual evoked-response (VER) and speechreading scores was investigated. A significant product-moment correlation of -.58 was obtained between the two measures, which confirmed the fundamental effect but was significantly weaker than that previously reported in the literature (-.90). Principal components analysis of the visual evoked-response waveforms revealed a previously undiscovered early VER component, statistically independent of the latency measure, which in combination with two other components predicted speechreading with a multiple correlation coefficient of S4. The potential significance of this new component for the study of individual differences in speechreading ability is discussed.

Validity of the Elderly Behavior Assessment for Relatives (EBAR)

2000 ◽  
Vol 16 (1) ◽  
pp. 77-83 ◽  
Author(s):  
Lina Pezzuti ◽  
Caterina Laicardi ◽  
Marco Lauriola
Keyword(s):  
Cognitive Functioning ◽  
Mini Mental State Examination ◽  
Rating Scale ◽  
Good Health ◽  
The Elderly ◽  
Behavior Assessment ◽  
Elderly Persons ◽  
Behavior Rating Scale ◽  
Components Analysis ◽  
State Examination

Summary: An Elderly Behavior Assessment for Relatives (EBAR), updating the GERRI ( Schwartz, 1983 ), was administered to relatives (or significant others) of 349 elderly persons, from 60 to over 80 years of age, living at home, in good health and without cognitive impairment. A trained psychologist administered subjects the Life Satisfaction for Elderly Scale (LSES), the Instrumental Activity of Daily Living (IADL), the Mini Mental State Examination (MMSE), and personally answered to an overall elderly behavior rating scale (RA). EBAR items were first examined. The more attractive and less discriminative statements were excluded. A principal components analysis was carried out on the remaining EBAR items. Three factors were extracted. After varimax rotation they were tentatively labeled: Everyday Cognitive Functioning, Depression, and Hostility. Factor-driven EBAR subscales were designed, taking into account simpler items in the factor matrix. Results provide evidence for EBAR construct validity. Everyday Cognitive Functioning is connected to the IADL and the RA scores; Depression is very highly related to the LSES; Hostility is weakly related to RA, IADL, and MMSE, indicating that the scale needs further investigation.

Psychometric Definition of Rorschach Determinant Component Structure

1998 ◽  
Vol 14 (2) ◽  
pp. 116-123 ◽  
Author(s):  
Raymond M. Costello
Keyword(s):  
Lower Order ◽  
Three Dimensions ◽  
Comprehensive System ◽  
Empirical Examination ◽  
Component Structure ◽  
Exner's Comprehensive System ◽  
Factor Analytic ◽  
Confirmatory Factor ◽  
Components Analysis ◽  
Definition Of

This is an empirical examination of Experienced Stimulation (es) and Experience Actual (EA) from Exner's Comprehensive System (CS) for Rorschach's Test, spurred by Kleiger's theoretical critique. Principal components analysis, Cronbach's α, and inter-item correlational analyses were used to test whether 13 determinants used to code Rorschach responses (M, FM, m, CF+C, YF+Y, C'F+C', TF+T, VF+V, FC, FC', FV, FY, FT) are best represented as a one, two, or more-dimensional construct. The 13 determinants appear to reflect three dimensions, a “lower order” sensori-motor dimension (m + CF+C + YF+Y + C'F+C' + TF+T + VF+V) with a suggested label of Modified Experienced Stimulation (MES), a “higher order” sensori-motor dimension (FM + FV + FY + FT) with a suggested label of Modified Experience Potential (MEP), and a third sensori-motor dimension (M+FC+FC') for which the label of Modified Experience Actual (MEA) is suggested. These findings are consistent with Kleiger's arguments and could lead to a refinement of CS constructs by aggregating determinants along lines more theoretically congruous and more internally consistent. A RAMONA model with parameters specified was presented for replication attempts which use confirmatory factor analytic techniques.

The Beck Hopelessness Scale

2016 ◽  
Vol 32 (2) ◽  
pp. 111-118 ◽  
Author(s):  
Marianna Szabó ◽  
Veronika Mészáros ◽  
Judit Sallay ◽  
Gyöngyi Ajtay ◽  
Viktor Boross ◽  
...  
Keyword(s):  
Binary Data ◽  
Factor Model ◽  
Clinical Sample ◽  
Analytical Techniques ◽  
Cross Cultural ◽  
Cultural Validity ◽  
Beck Hopelessness Scale ◽  
Method Effects ◽  
Hungarian Population ◽  
Components Analysis

Abstract. The aim of the present study was to examine the construct and cross-cultural validity of the Beck Hopelessness Scale (BHS; Beck, Weissman, Lester, & Trexler, 1974 ). Beck et al. applied exploratory Principal Components Analysis and argued that the scale measured three specific components (affective, motivational, and cognitive). Subsequent studies identified one, two, three, or more factors, highlighting a lack of clarity regarding the scale’s construct validity. In a large clinical sample, we tested the original three-factor model and explored alternative models using both confirmatory and exploratory factor analytical techniques appropriate for analyzing binary data. In doing so, we investigated whether method variance needs to be taken into account in understanding the structure of the BHS. Our findings supported a bifactor model that explicitly included method effects. We concluded that the BHS measures a single underlying construct of hopelessness, and that an incorporation of method effects consolidates previous findings where positively and negatively worded items loaded on separate factors. Our study further contributes to establishing the cross-cultural validity of this instrument by showing that BHS scores differentiate between depressed, anxious, and nonclinical groups in a Hungarian population.

Diagnoses Generated by Numerical Taxonomic Methods Applied to Standard Blood Variables

1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton
Keyword(s):  
Liver Cirrhosis ◽  
Renal Disease ◽  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Chronic Renal Disease ◽  
Function Analysis ◽  
Infectious Hepatitis ◽  
Components Analysis

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.

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