2. This can be checked by looking at scatterplots of pairs of variables. This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output. Click OK. Look at the output. 1.6The Output Viewer 1.7The Chart Editor 1.8Programming in SPSS 2 Data Description and Simple Inference for Continuous Data: The Lifespans of Rats and Ages at Marriage in the U.S. 2.1Description of Data 2.2Methods of Analysis. Allows you to select the method of factor rotation. Factor Analysis Researchers use factor analysis for two main purposes: Development of psychometric measures (Exploratory Factor Analysis - EFA) Validation of psychometric measures (Confirmatory Factor Analysis – CFA – cannot be done in SPSS, you have to use … This handout provides basic instructions on how to answer research questions and test hypotheses using linear regression (a technique which examines the … /C [0 0 0] endobj >> /Contents 26 0 R >> SPSS Tutorial AEB 37 / AE 802 Marketing Research Methods Week 7. %��������� Now, with 16 input variables, PCA initially extracts 16 factors (or “components”). 2. << /MediaBox [0 0 612 792] You can do this by clicking on the “Extraction” button in the main window for Factor Analysis (see Figure 3). /ProcSet [/PDF /ImageC /ImageI /Text] /MediaBox [0 0 612 792] 19 0 obj Correlation coefficients range from -1.0 (a perfect negative correlation) to positive 1.0 (a perfect positive correlation). >> /Resources << )’ + Running the analysis /P 5 0 R /Font 86 0 R Cluster analysis Lecture / Tutorial outline • Cluster analysis • Example of cluster analysis • Work on the assignment. Advanced Models module (Manual: SPSS 11.0 Advanced Models): This includes methods for ﬁtting general linear models and linear): /Metadata 4 0 R /ProcSet [/PDF /ImageC /ImageI /Text] You should also understand how to interpret the output from a multiple linear regression analysis. /Resources << endobj With both Pearson and Spearman, the … /Contents 51 0 R With ANOVA, the independent variable can have as many levels as desired. SPSS will not only compute the scoring coefficients for you, it will also output the factor scores of your subjects into your SPSS data set so that you can input them into other procedures. The closer correlation coefficients get to -1.0 or 1.0, the stronger the correlation. In the Factor Analysis window, click Scores and select Save As Variables, Regression, Display Factor Score Coefficient Matrix. How to Interpret SPSS Output Overview of SPSS Output. /Contents 34 0 R SPSS will extract factors from your factor analysis. How to interpret SPSS factor analysis output. In the ¯rst, one set of loadings ¯ ij. The interpretation of the Analysis Results has been presented in the next article. /XObject 79 0 R A sample of SPSS ANOVA … >> 3 0 obj /ColorSpace 38 0 R Factors will be located in the SPSS output file. application/pdf This method simplifies the interpretation of the factors. 8 0 obj READ PAPER. �а$*{fX�y����'(�K�+���u8 HE�;���0�!���{ig�1h���M��@4�آ���}\f
IBKO�+�="����������נ"�t���tp�@'*eK�t>s�I��'�͵Z��*�%BIVpz�z���z�?��]�R�Įp��m� /Kids [5 0 R 6 0 R 7 0 R 8 0 R 9 0 R 10 0 R 11 0 R 12 0 R 13 0 R 14 0 R 15 0 R 16 0 R 17 0 R 18 0 R 19 0 R 20 0 R] 2013-08-12T18:04:38+04:00 Be able explain the process required to carry out a Principal Component Analysis/Factor analysis. /XObject 65 0 R The number of factors “worth keeping” ranges 31 Full PDFs related to this paper. /ProcSet [/PDF /ImageC /ImageI /Text] Conducting a Path Analysis With SPSS/AMOS Download the PATH-INGRAM.sps data file from my SPSS data page and then bring it into SPSS. For general information regarding the similarities and differences between principal components analysis and factor analysis, see Tabachnick and Fidell (2001), for example. << 14 0 obj Factor Analysis Researchers use factor analysis for two main purposes: Development of psychometric measures (Exploratory Factor Analysis - EFA) Validation of psychometric measures (Confirmatory Factor Analysis – CFA – cannot be done in SPSS, you have to use e.g., Amos or Mplus). /Parent 3 0 R Obviously the variables must also be at least moderately correlated to each other, otherwise the number of factors will be almost the same … SPSS for Intermediate Statistics : Use and Interpretation. SPSS produces a lot of data for the one-way ANOVA test. /A << endobj Bartlett's test of sphericity tests the hypothesis that your correlation matrix is an identity matrix, which would indicate that your variables are unrelated and therefore unsuitable for structure detection. /Resources << Varimax Method. /Resources << Each component has a quality score called an Eigenvalue.Only components with high Eigenvalues are likely to represent a real underlying factor. More specifically, the goal of factor analysis is to reduce “the dimensionality of the original space and to give an interpretation to the new space, spanned by a reduced number of new dimensions which are supposed to underlie the old … Finally, we provide a careful explanation of each table and graph in the SPSS output. /Subtype /XML /MediaBox [0 0 612 792] Exploratory Factor Analysis Page 3 An output page will be produced… Minimize the output page and go to the Data View page. Ask for Pearson and Spearman coefficients, two-tailed, flagging significant coefficients. SPSS, R, SAS. >> For this reason, factor analysis usually proceeds in two stages. /ExtGState 84 0 R /Font 82 0 R The broad purpose of factor analysis is to summarize Download Full PDF Package. << If you do not know the number of factors to use, first perform the analysis … endobj << /Contents 73 0 R >> ad67e67a-05f6-11e3-0000-fdc1fd4f101a /Resources << �����u�}�-�X��|���W�q�_4�j��f������ˊ��kK��%5���v۟O�����V��˨ �"���G���9��e���Xx6�#�]-����6��i�]��
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2@�dQ1߾� ߩ��6(}���T�G���u�! A short summary of this paper. /Contents 59 0 R Method. /Pages 3 0 R /MediaBox [0 0 612 792] What Is Factor Analysis? /Parent 3 0 R /Parent 3 0 R /XObject 83 0 R Step 7: The next article will discuss the interpretation of its output i.e. /ProcSet [/PDF /ImageC /ImageI /Text] 2007. >> >> /Contents 63 0 R by carrying out a factor analysis on data from a study in the field of applied linguistics, using SPSS for Windows. The dependent (Y) variable is always ordinal or ratio data while the independent (X) variable is always nominal data (or other data that’s converted to be nominal). 1 Factor Analysis Factor analysis attempts to bring inter-correlated variables together under more general, underlying variables. /ColorSpace 89 0 R C8057 (Research Methods II Factor Analysis on SPSS Dr. Andy Field Page 5 1/6/2004 Interpreting Output from SPSS Select the same options as I have in the screen diagrams and run a factor analysis with orthogonal rotation. If the factor were measurable directly (which it >> /Parent 3 0 R /MediaBox [0 0 612 792] /Resources << Interpreting SPSS Correlation Output Correlations estimate the strength of the linear relationship between two (and only two) variables. /Filter [/FlateDecode] 6. Factor Analysis (EFA) How to run EFA in SPSS Interpreting Output of EFA in SPSS . data and getting SPSS to accomplish the analysis of the data. /Contents 44 0 R 18 0 obj /T (Tous) provides techniques for the analysis of multivariate data, speciﬁcally for factor analysis, cluster analysis, and discriminant analysis (see Chapters 11 and 12). /Resources << >> Finally, you should understand basic Microsoft Windows navigation operations: opening files and folders, saving your work, recalling previously saved work, etc. /ExtGState 66 0 R /Parent 3 0 R In the Factor Analysis window, click Scores and select Save As Variables, Regression, Display Factor Score Coefficient Matrix. /Parent 3 0 R /MediaBox [0 0 612 792] Interpretation of Factor Analysis using SPSS. x�}Y�$Ǒ�{�� �z�2"�`F0���j�#=��j6H�x�����m�qdduD�UՕV�nnf���{|�����i;��o�ákN���zm.g�����O�w�/�cۼ��9�?��������~h����v=5��q=��}���m�Lb��~���w��д�ۯ��h^��M�þk^�����#��ov��G��/��_+�����W_��~�`����o���_�����K?�#��Ҽ8I���������[��r�s�?��^硑y
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��nü�>ڳ,!�^J~�Q{۟:�T�ASr]i� >> /ProcSet [/PDF /Text] /ExtGState 71 0 R /NM (29b160e1-7a37-4f55-8b59c25bfce431f1) /Resources << Factor analysis and SPSS: Factor analysis can be performed in SPSS by clicking on “analysis” from menu, and then selecting “factor” from the data reduction option. /Creator (PrimoPDF http://www.primopdf.com) Statistical Analysis Using IBM SPSS – Factor Analysis Example- Supplementary Notes Page 3 V 2 = L 2 *F 1 + E 2 V 3 = L 3 *F 1 + E 3 Each variable is composed of the common factor (F 1) multiplied by a loading coefficient (L 1, L 2, L 3 - the lambdas) plus a unique or random component. Cross tabulation in SPSS: Interpretation of factor analysis using SPSS: Author; Recent Posts; Priya Chetty. /ProcSet [/PDF /ImageB /ImageC /ImageI /Text] /Contents 39 0 R /XObject 75 0 R OUTPUT 2: Kaiser and Bartlett test- The KMO statistic varies between 0 and 1. You should already know how to conduct a multiple linear regression analysis using SAS, SPSS, or a similar general statistical software package. example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided. Rotation. Figure 5 The first decision you will want to make is whether to perform a principal components analysis or a principal factors analysis. Deciding on the number of factors. /Font 35 0 R Interpretation of Factor Analysis using SPSS. In This Topic. /ExtGState 62 0 R /MediaBox [0 0 612 792] >> /Length 3354 IBM SPSS Statistics 23 is well-suited for survey research, though by no means is it limited to just this topic of exploration. ad67e67a-05f6-11e3-0000-fdc1fd4f101a PrimoPDF http://www.primopdf.com >> Newsom, Spring 2017, Psy 495 Psychological Measurement 14. endobj << >> … Be able to carry out a Principal Component Analysis factor/analysis using the psych package in R. Be able to demonstrate that PCA/factor analysis can be undertaken with either raw data or a set of … /Parent 3 0 R /ProcSet [/PDF /Text] /Border [0 0 0] example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided. /Subtype /Stamp Click Analyze, Correlate, Bivariate. << Finally, we provide a careful explanation of each table and graph in the SPSS output. /Parent 3 0 R Complete the following steps to interpret a factor analysis. This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output. 16 0 obj 2.3Analysis Using SPSS 2.3.1Lifespans of Rats 2.3.2Husbands and Wives 2.4Exercises 2.4.1Guessing the Width of a Lecture Hall 2.4.2 More on Lifespans of Rats: Signiﬁcance … /ProcSet [/PDF /ImageB /Text] /ProcSet [/PDF /ImageB /ImageC /ImageI /Text] Here one should note that Notice that the first factor accounts for 46.367% of the variance, the second 18.471% and the third 17.013%. THE THEORY BEHIND FACTOR ANALYSIS As the goal of this paper is to show and explain the use of factor analysis in SPSS, the The Result. Cluster interpretation through mean component values • Cluster 1 is very far from profile 1 (-1.34) and more similar to profile 2 (0.38) • Cluster 2 is very far from profile 5 (-0.93) and >> /Type /Page x��]ݳ%7q/��ޥ���$�s
1ܳ����0�@B�*�\�����T�*���*�i��Ԛ9g��~��t�����_��I��������ϾX�������/�==|���}�N���/�����+�p�����x�BXg���Խ������������o]^�iѫx�����ey����2����7/JMΨ���奛g�}xty��uu^?��C�]i�]y��奙�w�lѳ�|�A�n�5P�P,�+��&��b25�~//�.q�_]��}x�+�������e�ܺ��Ț���i�����FU@�{yI;��`���K���w!j-="��//������{n!ZⲨ�_��C�I[�����k���I�m���. /Rect [432 741.6 554.4 756] /ProcSet [/PDF /Text] /ExtGState 76 0 R /Contents 68 0 R /Type /Page /Subj (Stamp) endobj This presentation will explain … /N 90 0 R << Download PDF. /MediaBox [0 0 612 792] endobj The broad purpose of factor analysis is to summarize data so that relationships and patterns can be easily interpreted and … … 2. The variables used in factor analysis should be linearly related to each other. /Type /Page Statistics: 3.3 Factor Analysis Rosie Cornish. << [_b���n=3�pQWY��r��XMJ�Q��}U� c�l�X�PY7��/K��t��GMv]얣�:ݜ�'���\J;/��l�b�v�ǋ����2t��3@a>����y���h���8�}�)U��D�Q���x�ZT(���#��Yg� ]�Ѕ�FpV1*D�+Od��7.��t�y]H('�G��U��
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��O`O �v��?��F�Z�rG{���� ���� /Type /Page /C [1 0 0] /Type /Page /ExtGState 57 0 R To save space each variable is referred to only by … /Font 27 0 R /Type /Page 1 0 obj Home | Food and Agriculture Organization of the United Nations /ExtGState 28 0 R Chapter 17: Exploratory factor analysis Smart Alex’s Solutions Task 1 Rerun’the’analysis’in’this’chapterusing’principal’componentanalysis’and’compare’the’ results’to’those’in’the’chapter.’(Setthe’iterations’to’convergence’to’30. Specifically, suggestions for how to carry out preliminary procedures, EFA, and CFA are provided with SPSS and LISREL syntax examples. /Parent 3 0 R 2016-06-02T12:59:07-04:00 Assumptions: 1. /Type /Page PCA-SPSS.docx Principal Components Analysis - SPSS In principal components analysis (PCA) and factor analysis (FA) one wishes to extract from a set of p variables a reduced set of m components or factors that accounts for most of the variance in the p variables.In other words, we wish to reduce a set of p variables to a set of m underlying superordinate dimensions. endobj Typically, the mean, standard deviation and number of respondents (N ) who ... Lecture 11: Factor Analysis using SPSS 7 Rotated Component (Factor… The dialog box Extraction… allows us to specify the extraction method and the cut-off value for the extraction. /Type /Page A Simple Explanation… Factor analysis is a statistical procedure used to identify a small number of factors that can be used to represent relationships among sets of interrelated variables. /Count 16 Exploratory Factor Analysis An initial analysis called principal components analysis (PCA) is first conducted to help determine the number of factors that underlie the set of items PCA is the default EFA method in most … << 2 0 obj /Parent 3 0 R /Contents 81 0 R xD�M�z���7�Fʺ(�e]i}^4�E��(�����X+Y���Mn���>8��Wt�UxH�Ʞ2��WԼ`�wD6�����ga? /Parent 3 0 R /Author (cousined) /ColorSpace 67 0 R Key output includes factor loadings, communality values, percentage of variance, and several graphs. >> /Type /Catalog >> The general form of a bivariate regression equation is “Y = a + bX.” SPSS calls the Y variable the “dependent” variable and the X variable the “independent variable.” I think this notation is misleading, since regression analysis is frequently used with data collected by nonexperimental << /Length 5 0 R /Filter /FlateDecode >> /XObject 49 0 R /Contents 85 0 R PCA-SPSS.docx Principal Components Analysis - SPSS In principal components analysis (PCA) and factor analysis (FA) one wishes to extract from a set of p variables a reduced set of m components or factors that accounts for most of the variance in the p variables.In other words, we wish to reduce a set of p variables to a set of m underlying superordinate dimensions. If any are found then you should be aware that a problem could arise because of singularity in the data. >> Applying to graduate school: A test of the theory of planned behavior . Direct Oblimin Method. /ProcSet [/PDF /ImageC /Text] /Parent 3 0 R data and getting SPSS to accomplish the analysis of the data. /Font 30 0 R These loadings, how-ever, may not agreewith thepriorexpectations, or may not lend themselves to a reasonable interpretation. /ProcSet [/PDF /ImageC /Text] These underlying factors are inferred … Extraction. >> /Resources << /Type /Page Dummy variables can also be considered, but only in special cases. Here are the scoring coefficients: Look back at your data … /ColorSpace 43 0 R endobj >> << /Contents 29 0 R /Resources << /Resources << ��/���˯��+K~#^H��?�Vx��s��?��(��-�]�K�=��^��Y��o��)]�� /URI (http://dx.doi.org/10.20982/tqmp.09.2.p079) cousined An orthogonal rotation method that minimizes the number of variables that have high loadings on each factor. /MediaBox [0 0 612 792] /ExtGState 80 0 R /ExtGState 42 0 R Descriptives. /Contents 54 0 R is calculated which yields theoretical variances and covariances that ¯ttheobserved ones as closely as possible accordingtoacertain criterion. Be able to select and interpret the appropriate SPSS output from a Principal Component Analysis/factor analysis. /Font 55 0 R Interpretation of the Output Descriptive Statistics The first output from the analysis is a table of descriptive statistics for all the variables under investigation. Sample size: Sample size should be more than 200. Factor Analysis Rachael Smyth and Andrew Johnson Introduction Forthislab,wearegoingtoexplorethefactoranalysistechnique,lookingatbothprincipalaxisandprincipal /NM (8938fdc6-c49a-464c-8c4cfb08c893f3fa) If you are unsure how to interpret your PCA results, or how to check for linearity, carry out transformations using SPSS Statistics, or conduct additional PCA procedures in SPSS Statistics such as Forced Factor Extraction (see Step #4), we show you how to do this in our enhanced PCA guide. /Resources << Available methods are varimax, direct oblimin, quartimax, equamax, or promax. endobj For this to be understandable, however, it is necessary to discuss the theory behind factor analysis. << Be able to carry out a Principal Component Analysis factor/analysis using the psych package in R. To detect if a variable is a multivariate outlier, one must know the … >> << /ColorSpace 58 0 R /CreationDate (D:20160531153509-04'00') As for principal components analysis, factor analysis is a multivariate method used for data reduction purposes. Interpretation of output from SPSS OUTPUT 1: Scan the correlation coefficients and look for any greater than 0.9. /MediaBox [0 0 612 792] In this paper we have mentioned the procedure (steps) to obtain multiple regression output via (SPSS Vs.20) and hence the detailed interpretation of the produced outputs has been demonstrated. �����L��=~?f�W�}-|��"O�L܀�ͣ�{����+�I���� ��L�w_�:�菐�=Q`m�/Wr`������(��f��t����v��g]��{�� 況���/x�h`�-6ov�����͟ӧ�/��������n��ь;���z{ٷ��s�?_n�[�Ӿ��Nχ}+D�U���+Ƃ=3s�:��J��|�A���;kȵp��|���v���E�m�)vv@G��ۑ������s~U��Ǡ���Zw�����HX���f�W�g�o�qO�����1������~\{9�p�!��Ђ�����s�G?��S'�B�J 'N�����ҧ)�9rY�&�8�_���ޫ�9����,8�|Fd� �?1�jk�4�����{������E"3�$&���u�Pvc��Q|5e�(C��9:=B�Sp2a��4p ����������:
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