factor analysis

  1. R

    What does component signifies in Principal component analysis?

    Structure Matrix ......................................Component ...................................1 ..... 2 .....3 ......4 Eff_class.................. .893 .139 .236 .143 Prod_features.......... .889 -.194 .209 .219 offer......................... .912 .006 .486 .278 Brand_recognition...
  2. O

    confused about factor analysis output

    Hi, I have 100 participants answering an aesthetic scale ( 8 items in the scale) in my data. The question is "rate the following statements from 1= strongly disagree to 7= strongly agree". I copied 2 statements from my scale below. 1/Owning products that have superior designs makes me...
  3. S

    NO COMMON FACTOR VARIANCE in factoral analysis?

    Hi all, I have been told there is a term to describe the scenario when there is no (significant) common factor variance in a factor analysis model. I have tried googling this, and many connotations, as well as staring blankly at my screen with my eyes crossed just incase the answer were...
  4. E

    Using factor analysis to avoid Bonferroni death?

    Hi! I have a study with three dichotomous IVs and five DVs, which are brief, relatively reliable composite scales derived through factor analysis. If I run 2x2x2 ANOVAs for each of the individual subscales, I get great results, with interactions supporting my hypothesis. However, if I use a...
  5. S

    EFA: Factor Correlation Matrix Interpretation

    Hello, I recently ponder about the way to interpret the factor correlation matrix in an EFA (e.g. delivered in SPSS output). I realized that, despite the factor correlation matrix showing a negative correlation between two factors, these two factors may be positively related when I just...
  6. A

    Factor Analysis

    Hello! I run a Factor Analysis and got 14 factors with an Eigenvalue above 1! The first 5 factors explain most of the variance (Eigenvalue >2) and the remaining 9 factors have an eigenvalue around 1.5 What shall I do? Shall I keep all 14 factors or extract only the first 5 that explain...
  7. M

    Forward stepwise regression procedure: application to panel data

    I am in the process of evaluating the importance of some factors in predicting stock returns. In this context, I would like to implement the forward stepwise regression methodology. My dataset is comprised of 13,000 securities with monthly data from 1984 to 2012. Since this is my first...
  8. R

    Create 2 variable Bartlett factor score using maximum likelihood

    I'm working on research at the moment that has me creating factor scores from a variety of variables. One of my factor scores is based on only two measures: Variable's X and Y, lets say. I'd like to be able to create a Bartlett Factor score using Maximum Likelihood Estimation. When I run the...
  9. M

    Combining samples for EFA

    Hello, I have conducted an experiment in two different countries. The experiment included a survey. The same survey was used. Is it valid to combine the two sets to perform exploratory factor analysis, or there will be a scale effect (e.g. as in the case of logit choice models). Thank you
  10. D

    Factor Analysis: Creating Reliable Scales

    Hello all. I have a question I hope someone can help me with. I items which I have run PCA on and come up with 8 factors from about 20 vairables. I want to create a index to compare responses based on a classic political economic scale. i.e., some variables load heavily on items related to...
  11. S

    Factor Analysis with perfectly correlated variables

    Hi, FA#1: I ran a standard factor analysis in STATA (with varimax rotation) with 16 variables. Based on the Kaiser criteria I retain the 4 factors with eigenvalues > 1. FA#2: As a robustness test I included one variable twice and reran the same factor analysis with 17 variables. I now...
  12. S

    Interpreting the "Rotated component matrix" in Varimax Factor Analysis

    So I did Varimax factor analysis for 21 questions in order to group them. As per my understanding the rotated component matrix places each question to where it belongs which is either factor 1, factor 2 etc. Now two of the questions load under two exact factors: both load under factor 1 and...
  13. E

    Use of extracted factors from EFA with Mancova in SPSS

    For a 2x2 between subjects factorial analysis, I need to test interaction effects of 2 IVs each having 2 levels. The questionnaire has multiple items and I would first like to run FA to reduce DV data and further use it with Mancova. What needs to be achieved: 1. how the extracted data can be...
  14. M

    Collinearity Statistics Problem

    Hi everyone, I wonder if anyone would be able to help. I'm running multiple linear regressions and have two independent variables. When looking at the collinearity statistics values, tolerance is .999 for both variables and VIF is 1.001 for both variables as well, which just seems really weird...
  15. M

    reliability test for Factor analysis

    Hello friends, I am a green hand about the multivariate analysis, and I am having problem understanding the reliability test for Factor analysis. Silly it might sound. Is it for testing if the the data itself is reliable, or for testing if the data is reliable for the model, or for testing if...
  16. A


    Hi, I am a bit confused as to which variables should I include in the factor analysis. I have a huge questionnaire which i know i definitely should include to find the factors but im not sure whether I should include the demographics? Thank you in advance! Astero
  17. B

    Does SPSS give standardized factor scores?

    From the Johnson's book, I can see the orthogonal factor model is as follows: X−μ=LF+ϵ So if I use SPSS for extracting factor scores from a factor analysis of several variables, then am I going to get factor scores for mean subtracted variables? Actually my intention is to use the factor...
  18. B

    Confusions regarding Regression, Multicollinearity and Factor Analysis

    I am currently working with a data set that contains about 26 IVs of almost all sorts of scale of measurement (binary, nominal, ordinal and interval scale variables). There are strong reasons to suspect that some variables are probably highly correlated, while some may not be related to any...
  19. F

    Assumption of variables for Factor Analysis

    Hi, In wikipedia page of Factor Analysis it states:Suppose we have a set of p observable random variables. Does it mean that we can use this method only for data which are random variables?! http://en.wikipedia.org/wiki/Factor_analysis
  20. I

    Factor analysis step by step: PCA -> EFA -> CFA

    Hi all, I have read quite some literature now on factor analysis. But I can't seem to get my head around it and feel really inconfident in conducting such an analysis. Unfortunately I'm a bit on my own with regard to the analyses, so I hope to get some advice here. Most examples in textbooks...