Tagged Questions

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 ...

7 views

Equal variance assumption in factor analysis

How can we check this assumption? Sample variance? What if it doesn't hold? Do we have alternative?
86 views

CFA factor scores AMOS

I am conducting my confirmatory factor analysis (CFA) using AMOS, and respectivelly get the factor weights, the model fit, etc. However, is there a way in AMOS to export the actual factor scores for ...
59 views

What is Polychoric Correlation Coefficient intuitively?

There is clear meaning of Pearson product-moment correlation coefficient: it is cosine of angle between two vectors based on variables. Also there are 12 other ways to clearify the meaning of ...
24 views

Can I turn a latent variable be treated as an observed variable?

I am a doctoral candidate and for my dissertation research I am using two standardized scales as independent variables. Because these have not been used with my particular population, I needed to do ...
21 views

Factor analysis problems

I am completing a factor analysis with 105 items and am having some problems. When I look at the scree plot for the "elbow" it suggests that there a 5 factors, however these five factors only account ...
711 views

Skewed variables in factor analysis

I want to do principal component analysis (factor analysis) on SPSS based on 22 variables. However, some of my variables are very skewed (skewness calculated from SPSS ranges from 2–80!). So ...
21 views

How to calculate differential item functioning when factor structure differs between groups?

I want to test for differential item functioning on a self-report measure between two groups (i.e., one with a disease one without). Differential item functioning refers to a measurement bias wherein ...
3k views

Factor analysis of questionnaires composed of Likert items

I used to analyse items from a psychometric point of view. But now I am trying to analyse other types of questions on motivation and other topics. These questions are all on Likert scales. My initial ...
34 views

How to extract “MLR” fit measures generated by the Lavaan package of R

I am estimating some Confirmatory Factor Analysis (CFA) models using the Lavaan package and I hoping to extract the fitMeasures to export out of the model to a spreadsheet. This is easily done using ...
36 views

Calculating and using factor scores

I have performed a factor analysis of 14 binary items (Satisfactory vs Not Satisfactory) which yielded 2 factors with 7 items each. I am interested in creating simple factor scores by summing ...
19 views

Is factor analysis appropriate for repertory grid data?

I've used factor analysis for questionnaires and such before, but I have a new research question now and it doesn't seem like anything similar has been done. I've had participants rate 8 news articles ...
1k views

Whether to use original or reverse coded items in factor analysis?

I am currently analyzing data from a 34-item Likert scale. I already recoded the negatively stated variables in SPSS as different variables. I'm about to do a factor analysis. Should I use the ...
13 views

Tests if means between factors are significantly different

After performing a factor analysis and grouping a set of 20+ questions into 3 different factors, we can then calculate a mean, std dev etc for each of these sets of questions or in other words, per ...
735 views

Based on factor loadings (in factor analysis) can we give unequal weights to Likert scale items?

After gathering data, we compute score of any Likert (summative) scale (previously identified as factor in factor analysis) by adding up its individual item scores (and maybe dividing the sum by the ...
20 views

Factor analysis in Matlab [migrated]

I tried to perform a factor analysis with two significant factors. [Lambda, Psi] = factoran(R,2,'xtype','covariance') where matrix R is a 4x4 pairwise ...
62 views

How do I perform a multi-state decomposition with interaction effects?

I am trying to perform a decomposition with interaction effects. This paper provides a solution for n-factors where each factor has a binary state (see section 2). I have a problem with 2 factors, ...
43 views

253 views

Explanation of picking an orthogonal array in the Taguchi Method

I'm working on my thesis and I am trying to lower the amount of runs I need to do in an experiment so I thought I'd use the Taguchi method, however I don't understand how to use the selector table. ...
129 views

Reducing no of variables subsetted based on depth for PCA

First of all, sorry for the strange title, I had no idea how to describe my problem better. My issue is the following, I think it is pretty much limited to geosciences. I have several properties for ...
218 views

Dimensionality Reduction Algorithm for Large Dataset?

I have a reasonably large (5k variables x 120k cases) that I'd like to run a dimensionality reduction algorithm on. I tried doing a simple Factor Analysis on it in SPSS, but it (predictably) barfed on ...
4k views

How to perform principal components analysis on binary data (using SPSS)?

I have a dataset with a large number of Yes/No responses. Can I use principal components (PCA) or any other data reduction analyses (such as factor analysis) for this type of data? Please advise how I ...
13 views

Did anyone know how to fit factor analytic covriance struture either in R or SAS?

I would like to make meaningful interpretation from a two-way interaction data using factor analytic covariance structure. I have a genotype x environment matrix and I would like to know which ...
712 views

Differences on exploratory factor analysis, confirmatory factor analysis and principal component analysis

Before it is pointed, I am aware that a very similar question was already asked. Still, I am in doubt regarding the concept. More specifically, it is mentioned by the most voted answer that: In ...
138 views

What's the difference between a component and a factor in parallel analysis?

The psych package in R has a fa.parallel function to help determine the number of factors or components. From the documentation: ...
70 views

Why eigenvalues are greater than 1 in factor analysis?

Why we take eigenvalue greater than 1 in factor analysis to retain factors? And how can we decide which variables are to be chosen as factors?
24k views

What are the differences between Factor Analysis and Principal Component Analysis

It seems that a number of the statistical packages that I use wrap these two concepts together. However, I'm wondering if there are different assumptions or data 'formalities' that must be true to use ...
158 views

Can I categorize the factor scores to use them as predictors of an ordinal logistic regression?

I was wondering if I can categorize the factor saved scores by taking their quartiles (or some other measures, I am not sure what should I use!) as cut points and use them as predictors in an ordinal ...
227 views

What is the minimum sample size for using exploratory factor analysis to reduce a pool of questionnaire items?

Context: In my real experiment I am planning to include a questionnaire. I aim to measure 4 different constructs with multiple questions per construct. The questionnaire now consists of 24 items. I ...
48 views

Multi Factor analysis with FactoMineR

I have a database with different variables, both categorical and numerical. I wanted to analyse these using MultiFactor Analysis with FactoMineR, with the main idea to obtain which of them are the ...
88 views

What is a “factor” in Factor Analysis?

What is a factor from a linear algebra point of view? Is it a vector, matrix, basis, tuple, coordinate system or something else?
100 views

How to check if factor structures in two groups are similar?

After doing semantic differential experiment with two different group of people, there is need to do Factor Analysis, and after that to compare group's coordinates in factor space. I did factor ...
44 views

PCA or method of principal component for FA?

I have just read one of the answer from a member as follow: "One of the biggest reasons for the confusion between the two has to do with the fact that one of the factor extraction methods in Factor ...
84 views

Ideal number of variables for PCA analysis

I working with a dataset of around 4000 variables. I decided to carry out a PCA analysis for the data, but I am not quite sure about the suitable number of variables I should include in the test. ...
248 views

Should control variables be included in model if statistically insignificant?

I have a set of predictors in a linear regression, as well as three control variables. The issue here is that one of my variables of interest is only statistically significant if the control variables ...
55 views

Would rotation of extracted components/factors after PCA/EFA affect results of a subsequent regression analysis?

To use the scores of the extracted components/factors in a further regression analysis, like mixed effects model regression as predictors to an outcome variable or DV. Would be there any discrepancies ...
38 views

Kaiser's eigenvalue or MAP/parallel analysis?

i ran exploratory factor analysis and according to eigenvalue > 1, 41 factors were extracted out of 142 items. but when i ran MAP and parallel analysis, 16 factors were prescribed as a proper number ...
2k views

Factor analysis for ordinal variables that have different categories

I have a data set that contains about 40 categorical variables that are taken as independent variables (and believed to be related to some unobservable human resource factors) and 4 categorical ...
97 views

Maximum likelihood factor analysis fails

When trying to use maximum likelihood Factor analysis instead of Principle component analysis in SPSS, what are the reasons that I am unable to complete a factor extraction using maximum likelihood. ...
1k views

Best factor extraction methods, with reference to SPSS

SPSS offers several methods of factor extraction: Principal components (which isn't factor analysis at all) Unweighted least squares Generalized least squares Maximum Likelihood Principal Axis Alpha ...
93 views

Factor analysis at item or scale level?

To develop a new questionnaire for measuring lifeguards' vigilance, after gathering data from different literature, I found 20 scales contributing to lifeguards' vigilance. Then I started to design ...
224 views

Dynamic factor analysis vs state space model

The MARSS package in R offers function for dynamic factor analysis. In this package, the dynamic factor model is written as a special form of state space model and they assume the common trends follow ...
63 views

Confirmatory factor analysis for a newly constructed questionnaire

I am about to develop a new questionnaire with 142 questions I have performed exploratory factor analysis and 30 latent factors were extracted. I was wondering if it is necessary to perform ...
1k views

How to reduce number of items using factor analysis, internal consistency, and item response theory in conjunction?

I am in the process of empirically developing a questionnaire and I will be using arbitrary numbers in this example to illustrate. For context, I am developing a psychological questionnaire aimed at ...
74 views

Odd shift of statistical significance when some variables are dropped from model

I am testing the statistical significance of some explanatory variables in a factor model, using the Fama-MacBeth two-pass regression (also known as the Cross-Sectional Approach). Assuming my ...
23 views

One-item scale measure

I'm currently trying to investigate the different perception of outcome in telecommuting (working from home) and I am trying to compare the perception of job satisfaction, job performance and job ...
47 views

interpreting R lm(..) output when a variable is used as a factor [duplicate]

Below is a print screen of a summary(lm(..)). I called the response variable response explained by a continuous variable X and ...