scholarly journals Assessment of de-desertification approaches using multi-attribute decision making and principal factor analysis

2018 ◽  
Vol 06 (01) ◽  
pp. 229-254
Author(s):  
Mohammad Hassan Sadeghi Ravesh ◽  
Hassan Khosravi
Keyword(s):  
Decision Making ◽  
Factor Analysis ◽  
Principal Factor ◽  
Principal Factor Analysis ◽  
Multi Attribute Decision Making

Use of principal factor analysis to generate a corn silage fermentative quality index to rank well- or poorly preserved forages

2015 ◽  
Vol 96 (5) ◽  
pp. 1686-1696 ◽  
Author(s):  
Antonio Gallo ◽  
Gianluca Giuberti ◽  
Sara Bruschi ◽  
Paola Fortunati ◽  
Francesco Masoero
Keyword(s):  
Factor Analysis ◽  
Quality Index ◽  
Principal Factor ◽  
Corn Silage ◽  
Principal Factor Analysis

A robust version of principal factor analysis

COMPSTAT ◽  
2000 ◽  
pp. 385-390 ◽  
Author(s):  
G. Pison ◽  
P. J. Rousseeuw ◽  
P. Filzmoser ◽  
C. Croux
Keyword(s):  
Factor Analysis ◽  
Principal Factor ◽  
Principal Factor Analysis ◽  
Robust Version

Revision of the Brief Index of Self-Actualization

1998 ◽  
Vol 87 (1) ◽  
pp. 115-125 ◽  
Author(s):  
John R. Sumerlin ◽  
Charles M. Bundrick
Keyword(s):  
Factor Analysis ◽  
Principal Factor ◽  
Oblique Rotation ◽  
Principal Factor Analysis ◽  
Factor Loadings ◽  
Self Actualization

Items from the 40-item Brief Index of Self-actualization were submitted to principal factor analysis with promax and oblique rotation ( N = 620). With eigenvalues greater than 1 and factor loadings of .40 or higher, 32 items were retained as four factors, without overlap. A revised Brief Index of Self-actualization is presented as an improved measure of constructs underlying Abraham Maslow's description of a self-actualizing person.

An approach to the genesis of palygorskite in a Neogene-Quaternary continental basin using principal factor analysis

Clay Minerals ◽  
1995 ◽  
Vol 30 (3) ◽  
pp. 225-238 ◽  
Author(s):  
C. Sánchez ◽  
E. Galán
Keyword(s):  
Factor Analysis ◽  
Chemical Composition ◽  
Statistical Treatment ◽  
Principal Factor ◽  
Quaternary Sediments ◽  
Central Spain ◽  
Principal Factor Analysis ◽  
Lacustrine Basin ◽  
Marginal Areas ◽  
Continental Basin

AbstractThe Carrión lacustrine basin (≈10 km2), central Spain, is filled with Neogene-Quaternary sediments (20–25 m thick) rich in palygorskite. Two clay units of ∼15 m thick are of particular interest in the basin. The lower one contains over 75% phyllosilicates (palygorskite up to 90%, smectites and illite) in marginal areas (facies A), and it is laterally bound by a distal facies (B) also rich in clay minerals (smectites and illite, and some palygorskite) and gypsum, and includes dolomitic marl intercalations. The composition at the top is primarily marly, with some gypsum (C). The upper clay unit, mainly clay-size material, (D) is rich in smectites, palygorskite and sepiolite, and contains carbonate intercalations near the top. A statistical treatment of the mineralogical and chemical composition data from 120 samples, using principal factor analysis, suggests that: (a) illite and smectite are detrital in origin; (b) palygorskite was formed by transformation of illite and smectite involving reaction with Mg; and (c) sepiolite was a neoformation product favoured by evaporation of silica- and Mg-bearing waters.

On the Validity of the OOST Interest Inventory

1998 ◽  
Vol 86 (2) ◽  
pp. 614-614
Author(s):  
Stanley Oosthuizen
Keyword(s):  
Factor Analysis ◽  
Construct Validity ◽  
Physical Activities ◽  
Principal Factor ◽  
Varimax Rotation ◽  
Interest Inventory ◽  
Principal Factor Analysis ◽  
Chemistry Students

The Oost Interest Inventory was administered to 69 English, 126 Economy and 110 Chemistry students during 1993, to obtain information on construct validity. Except for the area Physical Activities all the differences between the means were significant. Product-moment correlations for related areas across instruments ranged from .15 to .66 and for unrelated areas from .03 to .14. Principal factor analysis with varimax rotation yielded three factors, namely, Arts, Science and Economy–Numbers.

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