Analisis Rotasi Ortogonal pada Teknik Analisis Faktor Menggunakan Metode Procrustes

Factor analysis is a multivariate statistical method that tries to explain the relationship between a number of independent variables by grouping these variables into factors. With this grouping, the existing variables will be easier to interpret. In increasing the power of factor interpretation, a matrix loading factor transformation must be performed. The transformation can be done by choosing the method that is in orthogonal rotation, the varimax or quartimax or equamax method. In order to find out which rotation techniques is the most appropriate, the minimum square distance values () generated from the procrustes method used. In this study three data were used from the results of the questionnaire, for data I obtain the value of the minimum distance squared with a varimax rotation that is with ; for data II obtain the value of the minimum distance squared with a quartimax rotation that is with ; for data III obtain the value of the minimum distance squared with a varimax rotation that is with .

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Harmful Chemicals in the Work Environment

Quality of Life (Banja Luka) - APEIRON ◽

10.7251/qol2001040i ◽

2020 ◽

Vol 18 (1-2) ◽

Author(s):

Predrag Ilić ◽

Dragana Nešković Markić ◽

Zia Ur Rahman Farooqi

Keyword(s):

Principal Component Analysis ◽

Factor Analysis ◽

Correlation Analysis ◽

Work Environment ◽

Statistical Method ◽

Principal Component ◽

Hospital Personnel ◽

Multivariate Statistical ◽

Multivariate Statistical Method ◽

Method Factor

For hospital personnel, a number of harmful chemicals exist. The paper deal with very different harmful chemicals, but all chemicals are important and continuing problems where the risks to health, if uncontrolled, are serious. In the research was used descriptive statistical operations and multivariate statistical method, factor analysis (FA), i.e. principal component analysis (PCA). An analysis of 24 organic and inorganic parameters was performed. Results of the correlation analysis suggest that these pollutants pairs might have similar sources or have been affected by similar factors. PCA she confirmed that the mutually correlated elements constitute a group of elements with a similar origin.

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Identification of the relationship between some characteristics of native walnut genotypes peculiar to Darende district of Malatya province: Use of factor analysis scores in multiple linear regression

Genetika ◽

10.2298/gensr1603923b ◽

2016 ◽

Vol 48 (3) ◽

pp. 923-932 ◽

Cited By ~ 3

Author(s):

Omer Beyhan ◽

Ecevit Eyduran ◽

Meleksen Akin ◽

Sezai Ercisli ◽

Kenan Gecer ◽

...

Keyword(s):

Factor Analysis ◽

Extraction Method ◽

Principal Component ◽

Kernel Weight ◽

Eastern Anatolia ◽

Factor Scores ◽

Varimax Rotation ◽

Independent Variables ◽

Selection Strategies ◽

The Relationship

Two main aims of this investigation were to predict kernel ratio (KR) and kernel weight (KW) from some walnut characteristics, respectively. For these aims, a total of 112 Walnut genotypes growing in nature were collected at Darende District of Malatya province in the Eastern Anatolia region of Turkiye. The walnut characteristics evaluated were nut length (NL), nut width (NW), nut height (NH), nut weight (NWe), shell thickness (ST), kernel ratio (KR) and kernel weight (KW), respectively. Independent variables were subjected to factor analysis based on principal component extraction method and VARIMAX rotation. On the basis of jointly using factor scores in multiple regression, KR (81.3 % R2 and 80.6 % adjusted R2) and KW (94.7% R2 and 94.5% adjusted R2) characteristics were predicted by using four factor scores with a big accuracy without multicollinearity problem. Consequently, the present results revealed that, walnuts of heavier KW and NWe in the prediction of KR would be expected to produce those of higher KR, and walnuts of higher values in NH, NW, NWe, ST, NL, and KR in the prediction of KW would be expected to produce those of heavier KW. The knowledge may help walnut breeders to improve new selection strategies.

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