Factor analysis is a data reduction technique which replaces inter-correlating variables by a smaller number of continuous latent variables called factors. The factors are believed to be responsible for the inter-correlations. For confirmatory factor analysis, please use tag confirmatory-factor. For ...

learn more… | top users | synonyms (1)

0
votes
0answers
7 views

How to compute a latent variable (as a composite index)

Can I calculate a latent variable (construct) after the formula: Sum of (summated scale for factor i * variance explained by factor i), i taking values from 1 to n (n being the number of factors)? Or ...
0
votes
0answers
11 views

Summated scales for factors (latent variables)

For summated scales: can I use all the variables that load on a factor or is it necessary to use only the variables with high loading (over 0.70, for example)?
0
votes
0answers
14 views

Loadings in factor analysis

If I have a sample of over 350 respondents, is it acceptable to consider loadings over 0.50 as being practically significant or should I consider loadings over 0.30 as being significant (which would ...
0
votes
0answers
11 views

Criteria for deleting variables in factor analysis [duplicate]

Does it have importance in conventional PCA/factor analysis which of the criteria: communality and loading problems is taken into consideration for deleting variables in the conventional PCA/factor ...
0
votes
0answers
4 views

Summated scales (after factor analysis)

Is it okay to calculate summated scales if I am undertaking an exploratory study and some of the factors that result are somewhat different from what I have found in the literature? (I have read that ...
0
votes
0answers
7 views

Combining CATPCA with conventional PCA or factor analysis

I have some concerns regarding factor analysis and especially about combining the factor analysis for an ordinal scale (categorical data) - CATPCA with conventional PCA or with factor analysis. ...
2
votes
0answers
48 views

Factor analysis - CATPCA combined with conventional PCA

I have some concerns regarding factor analysis and especially about combining the factor analysis for an ordinal scale (categorical data) - CATPCA with conventional PCA. Basically, I need to enter my ...
0
votes
0answers
27 views

Creating index from three variables in panel data

I have three variables which I want to combine in one. The obvious choice is factor analysis or principal component analysis but it's not so simple with panel data because it needs means and standard ...
4
votes
1answer
43 views

Principal component regression analysis using SPSS

I have done multiple regression analysis (MLR) of my data and find out $R^2$ and $r$, and then to remove multicollinearity problem I used PCA. This analysis generated PC equal to my variables, I ...
0
votes
0answers
25 views

Object 'w' not found error in factor analysis with package 'psych' [migrated]

A lot of questions about factor analysis on these pages. I have browsed through them but nothing seems similar, so hopefully someone can help. I am running a factor analysis on some survey questions ...
0
votes
0answers
10 views

Scores derived from variance specific for a factor

I received a comment about my article from one of the reviewer but I do not understand what I should do. Here is a short explanation of the study: This study investigated the influence of lectures ...
0
votes
1answer
32 views

Eliminated items in Factor Analysis

I'd like to get your opinions on how to interpret items that had to be eliminated in factor analysis (FA). I've been researching consumer shopping motivations and ran a survey with 40 items, which ...
-1
votes
1answer
53 views

factor analysis for given data with help of matlab

suppose that we have following data i have done covariance matrix and eigenvalue decomposition ...
1
vote
0answers
12 views

What is the relationship between scale reliability measures (Cronbach's alpha etc.) and component/factor loadings?

Let's say I have a dataset with scores on a bunch of questionnaire items, which are theoretically comprised of a smaller number of scales, like in psychology research. I know a common approach here ...
1
vote
1answer
147 views

Steps done in factor analysis compared to steps done in PCA

I know basically how to express PCA (Principal component analysis) mathematicaly, but I would like to know steps that should be used for factor analysis. ...
0
votes
0answers
19 views

Determining characteristics of sampling sets for EFA/CFA/SEM

Dividing sample data into several sets seems to be a common approach in statistics. This is especially evident in predictive modeling, where samples are traditionally divided into two sets, usually ...
0
votes
1answer
38 views

Factor analysis Vs PCA [closed]

Which is a better method of data reduction - factor analysis or principal component analysis?
0
votes
0answers
22 views

Factor analysis using principal component method [duplicate]

Is factor analysis using principal component method the same as principal component analysis?
0
votes
0answers
10 views

Can non-normal data be used for factor analysis? [duplicate]

I would like to do factor analysis to derive a nutrient intake pattern. Many of these variables are not normally distributed. Is it gonna be a problem? And there are just 7 variables available. Can ...
0
votes
0answers
14 views

Implications of doing a confirmatory factor analysis with a correlation matrix as input instead of a variance-covariance matrix?

Is this possible, and if so what are the implications of doing things one way rather than another. Is one approach generally preferable? So far I have only been taught to use a variance-covariance ...
2
votes
1answer
59 views

Why is it wrong to discover factors using EFA then use CFA on the same data to confirm that factor model?

I understand that it's instead correct to cross-validate using new data. Why is it so? It is just that a model will tend to fit the data set that was used to created it better than another randomly ...
0
votes
0answers
69 views

How to interpret and code semantic differential scale into SPSS?

Is the semantic differential rating scale below considered a scale of intensity? This is a sample of 7 items contained in a group PQ. Legend: 1 and 7: (extremely), 2 and 6: (moderately), 3 and ...
1
vote
0answers
18 views

Do we need to check Internal Consistency of Validated Questionnaire?

Do I need to necessarily conduct a reliability test to determine the internal consistency of the items in a questionnaire that I have adopted, even though that instrument had already been validated ...
0
votes
0answers
17 views

How to model the factors extracted from factor analysis with multinomial response

I want to model the 5 factors obtained from factor analysis with multinomial response. I calculated the factor scores by taking the mean of the raw scores of correlated variables in a factor. When I ...
0
votes
0answers
42 views

Number of observations needed to perform pca

I read in this paper (page 3) comparing pca to factor analysis that both methods need a number of observations about 5 times the number of variables. Why? and how would you reduce the number of ...
0
votes
1answer
45 views

Interpreting results of a factor analysis

I performed factor analysis on R using factanal. Following advice I found on this tutorial, I chose the number of factors as being the number of principal components that capture 90% of the ...
0
votes
1answer
30 views

Choosing a score for factor analysis

I want to perform factor analysis to reduce the number of variables in my dataset (the variables are very redundant). One of the parameters I need to supply to the R code is the number of factors to ...
1
vote
0answers
23 views

How to create item parcels for a factor that is not unidimensional?

This is follow-up question by "How to create item parcels in SPSS Amos?" My question is how to create item parcels for a factor that is not a unidimensional. Several articles have mentioned that ...
1
vote
2answers
63 views

Is it legitimate to use factor analysis or clustering before regression

My goal is to make a logistic regression. The DV is a yes or no variable, and I already found 3 significant IV in my model. ...
6
votes
3answers
94 views

How to correctly interpret a parallel analysis in exploratory factor analysis?

Some scientific papers report results of parallel analysis of principal axis factor analysis in a way inconsistent with my understanding of the methodology. What am I missing? Am I wrong or are they. ...
0
votes
0answers
44 views

Factor analysis using spss

I got determinant value– 5.84E-007. What does it mean? Should I continue the work or not? What do I have to do? And also I obtain the following Kaiser-Meyer-Olkin value and Bartlett's Test results ...
1
vote
0answers
10 views

Statistical technique to assess nutrition

My goal is to find risk factors for a disease. I think that a malnutrition is a risk factor for this disease. I have 5 variables that indicate the frequencies of ...
0
votes
1answer
39 views

factor analysis: can irrelevant factors be identified by tweaking FA options?

So I ran a factor analysis (principal components method) on a dataset, first using the correlation matrix and then using the covariance matrix, both with varimax rotations. The results of both factor ...
1
vote
1answer
45 views

Place of 'Number of Factors' determination in EFA Decision Sequence

I've checked two textbooks about EFA, one is the seminal work of Gorsuch (1974, 'Factor Analysis') and the other 'Exploratory and Confirmatory Factor Analysis' by Thompson (2004). Both described ...
1
vote
1answer
51 views

Computing composite score from variables that do not follow a likert scale

I am trying to develop a regression-weighted composite score. I have 4 variables a, b, c, d that are not necessarily linearly related that I would like to transform to A, B, C, D such that I can ...
2
votes
0answers
32 views

What to do when exploratory factor analysis results are different for complete-cases and imputed data?

I have a hundred items that I'm performing EFA on, with around 370 complete cases. Using parallel analysis to determine the number of factors to extract, EFA gave 9 factors, all of which make ...
1
vote
2answers
43 views
2
votes
2answers
113 views

Is common factor analysis ever performed using the covariance matrix?

Common factor analysis entails the eigendecomposition and subsequent interpretation of $\mathbf{C}$ which is often described the correlation matrix with the diagonal elements replaced with approximate ...
0
votes
2answers
60 views

factor analysis problem in structural equation model

I am using an Extended Technology Acceptance Model and have adopted an instrument from a research paper. After performing factor analysis in SPSS, most questions related to different constructs ...
0
votes
1answer
42 views

Which component to choose when variable load heavily on more than one component

I am doing factor analysis with Principal component extraction method. Below is the Structure matrix Extraction method: PCA Rotation method: Promax with kaiser normalization ...
0
votes
1answer
27 views

Outliers and Linearity for EFA

I am having 56 likert scaled items for IV and 28 likert scaled items for dv. As to fulfill the assumption for EFA, outliers and linearity need to be checked. Can anyone tells me what method/analysis ...
0
votes
0answers
39 views

spss principal axis factoring output problem

I am trying to run a factor analysis (SPSS) using principal axis factoring with an oblique (or promax) rotation because the variables are highly correlated. However, the output for "total variance ...
13
votes
1answer
396 views

How does Factor analysis explain the covariance and PCA explains the variance?

As I read in Bishop's PRML (here is the clip of that part about FA): According to the highlighted part, factor analysis captures the covariance between variables in the matrix $W$. I wonder HOW? ...
0
votes
0answers
17 views

Forced-choice data possible with confirmatory factor analysis?

I have a task where I ask participants to view a series of images. After viewing each image they are given several options with which they must a forced-choice as to which category the image falls ...
0
votes
1answer
87 views

EFA: Can I remove/drop variables with non significant loadings and re-run the EFA?

I am employing EFA to 56 items. However, there were cross-loadings occurred and, therefore decision to drop the items is made. The question: The rotated components matrix showed there were a few items ...
1
vote
0answers
21 views

Which Non-parametric test to use with two Ordinal sets of data

I am trying to find which factors in Ques 6 are strongly related to company being rated high as compared to others in Ques 4 and similarly factors related to company being rated low.
2
votes
0answers
21 views

Factors with only two variables in factor analysis

I am running a factor analysis and have a couple of questions. I have 10 variables, all of them come from a survey, with each answer is in the scale of 1 to 7. I have calculated a correlation matrix ...
1
vote
1answer
53 views

Correlating two questionnaires with grouped items

I need to correlate employee engagement (gathered data using the 9 item UWES questionnaire) and organizational commitment (gathered data using the 18 item Organizational Commitment Scale). The both ...
3
votes
1answer
308 views

PCA and exploratory Factor analysis on the same data set

I would like to know if it makes any logical sense to perform principal component analysis (PCA) and exploratory factor analysis (EFA) on the same data set. I have heard professionals expressly ...
0
votes
2answers
100 views

Confirmatory Factor Analysis with R lavaan

I tried to do a CFA with the lavaan package in R. Here is my model: I know how to define my latent variables like this: ...