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Journal articles on the topic 'Factor analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Kratochvíl, Petr. "The determination of factors in linear models of factor analysis." Applications of Mathematics 35, no. 5 (1990): 350–55. http://dx.doi.org/10.21136/am.1990.104416.

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2

Majumdar, Dr Kakali. "Factor Analysis and Business Research." Indian Journal of Applied Research 1, no. 6 (2011): 151–54. http://dx.doi.org/10.15373/2249555x/mar2012/52.

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3

Dr.G.Kalaivanan, Dr G. Kalaivanan, and B. Ussaima B.Ussaima. "Factors Attracting Children to View TV Commercials - A Study Using Factor Analysis." Indian Journal of Applied Research 4, no. 6 (2011): 71–73. http://dx.doi.org/10.15373/2249555x/june2014/21.

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4

Gurčík, Ľ., and V. Jančíková. "Factor analysis of owners equity effectiveness." Agricultural Economics (Zemědělská ekonomika) 48, No. 5 (2012): 229–32. http://dx.doi.org/10.17221/5308-agricecon.

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The paper shows methodical procedure and results of factor analysis of owners equity effectiveness in form of quantification and determination of analytical indicators of their pyramidal system. The analysis is realised through comparison of aggregated values of two groups of enterprises (per 30 each group) for the period 1998&ndash;2000. First group of enterprises is in the first third of soil price groups in Slovakia (cheapest soil) and the second group in the third of price group of the most expensive soil.

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5

Raghuvanshi, Monika. "Attitude Exploration Using Factor Analysis Technique." unibulletin 5, no. 1-2 (2016): 13–25. http://dx.doi.org/10.22521/unibulletin.2016.512.2.

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6

Maman, Abdurrohman, and Marsus Soffan. "Factor Analysis for Slow Budget Realization." INTERNATIONAL JOURNAL OF INNOVATION AND ECONOMIC DEVELOPMENT 3, no. 1 (2017): 28–50. http://dx.doi.org/10.18775/ijied.1849-7551-7020.2015.31.2002.

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The government of Indonesia has long experienced an uneven pattern of budget realization. Our budget realization is characterized by small absorption in the first three-quarters and then piled up in the last quarter. An increase in spending at the end of the year eventually led to the quality of work on the national economy, which is not considered optimal. Through factor analysis, the researchers reviewed what factors are causing slow realization of the budget, especially for spending unit in the working area of KPPN Jakarta II. Several studies have been conducted to determine the problem, in

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7

Jones, Roger. "Factor Analysis." British Journal of General Practice 68, no. 674 (2018): 403. http://dx.doi.org/10.3399/bjgp18x698417.

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8

Armstrong, Diane. "Factor analysis." Nursing Standard 14, no. 48 (2000): 25. http://dx.doi.org/10.7748/ns.14.48.25.s36.

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9

Sushmita, Rani,. "Factor Analysis:." DIU Journal of Humanities and Social Science 5, no. 1 (2017): 57–68. http://dx.doi.org/10.36481/diujhss.v.05i1.gasrn795.

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The principal purpose of this study is to identify and analyze the factors responsible for poor listening skill of Bangladeshi EFL learners.The study was conducted from 01 March 2015 to 25 May 2017. Thirty-two variables which are mostlyresponsible for poor listening skill are selected from related literature and the researcher’s own experience in teaching EFL learners. Factor analysis has been conducted to reduce the amount of the total variables, to identify the important variables and to arrange them into useful categories. SPSS 16 has been used to analyze the data collected from the primary

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10

Robinson, Lawrence R., Deborah E. Rubner, Patricia W. Wahl, Wilfred Y. Fujimoto, and Walter C. Stolov. "FACTOR ANALYSIS." American Journal of Physical Medicine & Rehabilitation 71, no. 1 (1992): 22–27. http://dx.doi.org/10.1097/00002060-199202000-00006.

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11

Gregson, Ken. "Factor analysis." Work Study 42, no. 1 (1993): 10–11. http://dx.doi.org/10.1108/eum0000000002688.

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12

Stewart, David, James Barnes, Joseph Cote, Robert Cudeck, and Edward Malthouse. "Factor Analysis." Journal of Consumer Psychology 10, no. 1-2 (2001): 75–82. http://dx.doi.org/10.1207/s15327663jcp1001&2_07.

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13

Fearn, Tom. "Factor Analysis." NIR news 24, no. 8 (2013): 26–27. http://dx.doi.org/10.1255/nirn.1409.

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14

Fukunaka, Kosuke, and Hideki Toyoda. "Analysis of Unique Factor Structures in Factor Analysis." Japanese Journal of Personality 20, no. 2 (2011): 98–109. http://dx.doi.org/10.2132/personality.20.98.

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15

Soewin, E., and T. Chinda. "Factors affecting construction performance: exploratory factor analysis." IOP Conference Series: Earth and Environmental Science 140 (April 2018): 012102. http://dx.doi.org/10.1088/1755-1315/140/1/012102.

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16

Jun Li and Dacheng Tao. "Exponential Family Factors for Bayesian Factor Analysis." IEEE Transactions on Neural Networks and Learning Systems 24, no. 6 (2013): 964–76. http://dx.doi.org/10.1109/tnnls.2013.2245341.

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17

Bentler, Peter M., and Jan de Leeuw. "Factor Analysis via Components Analysis." Psychometrika 76, no. 3 (2011): 461–70. http://dx.doi.org/10.1007/s11336-011-9217-5.

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18

M, Deepan, Deepa N, Rohini A, Malarkodi M, and Indumathi VM. "Factors influencing mutual fund investment decisions-factor analysis." International Journal of Chemical Studies 8, no. 1 (2020): 2106–9. http://dx.doi.org/10.22271/chemi.2020.v8.i1ae.8578.

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19

Le, Thu, Daniel Bolt, Eric Camburn, Peter Goff, and Karl Rohe. "Latent Factors in Student–Teacher Interaction Factor Analysis." Journal of Educational and Behavioral Statistics 42, no. 2 (2017): 115–44. http://dx.doi.org/10.3102/1076998616676407.

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Classroom interactions between students and teachers form a two-way or dyadic network. Measurements such as days absent, test scores, student ratings, or student grades can indicate the “quality” of the interaction. Together with the underlying bipartite graph, these values create a valued student–teacher dyadic interaction network. To study the broad structure of these values, we propose using interaction factor analysis (IFA), a recently developed statistical technique that can be used to investigate the hidden factors underlying the quality of student–teacher interactions. Our empirical stu

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20

Parmet, Yisrael, Edna Schechtman, and Michael Sherman. "Factor Analysis Revisited – How Many Factors are There?" Communications in Statistics - Simulation and Computation 39, no. 10 (2010): 1893–908. http://dx.doi.org/10.1080/03610918.2010.524332.

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21

Chen, Dachuan, Wenqi Lu, and Siyu Xie. "High frequency factor analysis with partially observable factors." Journal of Econometrics 251 (September 2025): 106058. https://doi.org/10.1016/j.jeconom.2025.106058.

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22

Onatski, Alexei, and Chen Wang. "Spurious Factor Analysis." Econometrica 89, no. 2 (2021): 591–614. http://dx.doi.org/10.3982/ecta16703.

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This paper draws parallels between the principal components analysis of factorless high‐dimensional nonstationary data and the classical spurious regression. We show that a few of the principal components of such data absorb nearly all the data variation. The corresponding scree plot suggests that the data contain a few factors, which is corroborated by the standard panel information criteria. Furthermore, the Dickey–Fuller tests of the unit root hypothesis applied to the estimated “idiosyncratic terms” often reject, creating an impression that a few factors are responsible for most of the non

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23

Gampp, Harald, Marcel Maeder, Charles J. Meyer, and Andreas D. Zuberbuehler. "Evolving Factor Analysis." Comments on Inorganic Chemistry 6, no. 1 (1987): 41–60. http://dx.doi.org/10.1080/02603598708081852.

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24

Schostack, K., P. Parekh, S. Patel, and E. R. Malinowski. "Evolutionary factor-analysis." Journal of Research of the National Bureau of Standards 93, no. 3 (1988): 256. http://dx.doi.org/10.6028/jres.093.035.

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25

FERKETICH, SANDRA, and MARY MULLER. "Factor Analysis Revisited." Nursing Research 39, no. 1 (1990): 59. http://dx.doi.org/10.1097/00006199-199001000-00012.

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26

Reio, Thomas G., and Brad Shuck. "Exploratory Factor Analysis." Advances in Developing Human Resources 17, no. 1 (2014): 12–25. http://dx.doi.org/10.1177/1523422314559804.

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27

Muthén, Bengt O. "Tobit factor analysis†." British Journal of Mathematical and Statistical Psychology 42, no. 2 (1989): 241–50. http://dx.doi.org/10.1111/j.2044-8317.1989.tb00913.x.

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28

Attias, H. "Independent Factor Analysis." Neural Computation 11, no. 4 (1999): 803–51. http://dx.doi.org/10.1162/089976699300016458.

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We introduce the independent factor analysis (IFA) method for recovering independent hidden sources from their observed mixtures. IFA generalizes and unifies ordinary factor analysis (FA), principal component analysis (PCA), and independent component analysis (ICA), and can handle not only square noiseless mixing but also the general case where the number of mixtures differs from the number of sources and the data are noisy. IFA is a two-step procedure. In the first step, the source densities, mixing matrix, and noise covariance are estimated from the observed data by maximum likelihood. For t

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29

Tolkoff, Max R., Michael E. Alfaro, Guy Baele, Philippe Lemey, and Marc A. Suchard. "Phylogenetic Factor Analysis." Systematic Biology 67, no. 3 (2017): 384–99. http://dx.doi.org/10.1093/sysbio/syx066.

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30

Pison, Greet, Peter J. Rousseeuw, Peter Filzmoser, and Christophe Croux. "Robust factor analysis." Journal of Multivariate Analysis 84, no. 1 (2003): 145–72. http://dx.doi.org/10.1016/s0047-259x(02)00007-6.

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31

WATSON, ROGER. "Exploring factor analysis." Journal of Psychiatric and Mental Health Nursing 3, no. 1 (1996): 75. http://dx.doi.org/10.1111/j.1365-2850.1996.tb00198.x.

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32

Manne, Rolf, Hailin Shen, and Yizeng Liang. "Subwindow factor analysis." Chemometrics and Intelligent Laboratory Systems 45, no. 1-2 (1999): 171–76. http://dx.doi.org/10.1016/s0169-7439(98)00101-4.

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33

Mason, Caroline, Marcel Maeder, and Andrew Whitson. "Resolving Factor Analysis." Analytical Chemistry 73, no. 7 (2001): 1587–94. http://dx.doi.org/10.1021/ac991141q.

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34

Lewin-Koh, S. C. "Heteroscedastic factor analysis." Biometrika 90, no. 1 (2003): 85–97. http://dx.doi.org/10.1093/biomet/90.1.85.

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35

Srivastava, Sanvesh, Barbara E. Engelhardt, and David B. Dunson. "Expandable factor analysis." Biometrika 104, no. 3 (2017): 649–63. http://dx.doi.org/10.1093/biomet/asx030.

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36

Emerson, Robert Wall. "Exploratory Factor Analysis." Journal of Visual Impairment & Blindness 111, no. 3 (2017): 301–2. http://dx.doi.org/10.1177/0145482x1711100313.

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37

Klami, Arto, Seppo Virtanen, Eemeli Leppaaho, and Samuel Kaski. "Group Factor Analysis." IEEE Transactions on Neural Networks and Learning Systems 26, no. 9 (2015): 2136–47. http://dx.doi.org/10.1109/tnnls.2014.2376974.

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38

Ismail, K. "Unravelling factor analysis." Evidence-Based Mental Health 11, no. 4 (2008): 99–102. http://dx.doi.org/10.1136/ebmh.11.4.99.

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39

Keller, H. R., and D. L. Massart. "Evolving factor analysis." Chemometrics and Intelligent Laboratory Systems 12, no. 3 (1991): 209–24. http://dx.doi.org/10.1016/0169-7439(92)80002-l.

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40

Hong, Sungjin. "Warped factor analysis." Journal of Chemometrics 23, no. 7-8 (2009): 371–84. http://dx.doi.org/10.1002/cem.1231.

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41

Kosfeld, Reinhold, and Jørgen Lauridsen. "Factor analysis regression." Statistical Papers 49, no. 4 (2006): 653–67. http://dx.doi.org/10.1007/s00362-006-0036-1.

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42

Nakano, Takahiro, Tsuyoshi Yamada, and Takahiko Nishijima. "Factor structural analysis of condition fluctuation by dynamic factor analysis." Taiikugaku kenkyu (Japan Journal of Physical Education, Health and Sport Sciences) 48, no. 4 (2003): 369–81. http://dx.doi.org/10.5432/jjpehss.kj00003390829.

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43

Devasena, Dr S. Valli. "Physical Evidence –A Part of Customer Satisfaction An Analysis Using Factor Analysis." Indian Journal of Applied Research 3, no. 12 (2011): 87–90. http://dx.doi.org/10.15373/2249555x/dec2013/23.

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44

G., Ramesh Pandi. "Attitude of Retailers towards Green Marketing Practices: Analysis through Factor Analysis and Cluster Analysis Techniques." International Journal of Psychosocial Rehabilitation 24, no. 5 (2020): 3595–608. http://dx.doi.org/10.37200/ijpr/v24i5/pr202068.

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45

Makhmanazarovna, Ravshanova Mukhayyo. "Skills required to perform two-factor econometric analysis." European International Journal of Pedagogics 5, no. 1 (2025): 52–53. https://doi.org/10.55640/eijp-05-01-10.

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In this article, the author provides information on the selection of factors, the implementation of correlation and regression analysis. The construction of an econometric model is shown step by step. Information is also provided on the stage of generating a regression equation using correlation coefficients and a system of normal equations.

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46

Boyanov, Petar. "IMPLEMENTATION OF FACTOR ANALYSIS IN THE OPTICAL MANIFACTURING." Journal Scientific and Applied Research 8, no. 1 (2015): 16–20. http://dx.doi.org/10.46687/jsar.v8i1.173.

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A model of factor analysis is developed in the process of designing of complex optical systems. Factor analysis is indispensable in designing of photometric and spectrophotometric optical-electronic devices which consist of entrance-scanning system by space, lens with inner focusing, collimator objective which ensure the entering of a parallel bundle of rays over a dispersing diffraction grate over a wave length, a chamber lens and respectively, a sensor. These and similar optical systems require higher degree of elimination of chromatic aberration, etc. which ensures good quality of the optic

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47

Pattnaik, Sudhanshu. "An Empirical Investigation into the Factors Influencing While Purchasing Car in India-A Confirmatory Factor Analysis." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10-SPECIAL ISSUE (2019): 404–10. http://dx.doi.org/10.5373/jardcs/v11sp10/20192821.

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48

Gniazdowski, Zenon. "Principal Component Analysis versus Factor Analysis." Zeszyty Naukowe WWSI 15, no. 24 (2021): 35——88. https://doi.org/10.26348/znwwsi.24.35.

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The article discusses selected problems related to both principal component analysis (PCA) and factor analysis (FA). In particular, both types of analysis were compared. A vector interpretation for both PCA and FA has also been proposed. The problem of determining the number of principal components in PCA and factors in FA was discussed in detail. A new criterion for determining the number of factors and principal components is discussed, which will allow to present most of the variance of each of the analyzed primary variables. An efficient algorithm for determining the number of factors in F

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49

Adachi, Kohei. "SOME CONTRIBUTIONS TO DATA-FITTING FACTOR ANALYSIS WITH EMPIRICAL COMPARISONS TO COVARIANCE-FITTING FACTOR ANALYSIS ." Journal of the Japanese Society of Computational Statistics 25, no. 1 (2012): 25–38. http://dx.doi.org/10.5183/jjscs.1106001_197.

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50

Uno, Kohei, Kohei Adachi, and Nickolay T. Trendafilov. "Clustered Common Factor Exploration in Factor Analysis." Psychometrika 84, no. 4 (2019): 1048–67. http://dx.doi.org/10.1007/s11336-019-09666-5.

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