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].

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Principal Component Analysis in SPSS and Stata - very different results

For my PhD thesis I have to do a Principal Component Analysis (PCA). I didn't find it too difficult in Stata and was happy interpreting the results (I know there is a difference between factor and ...
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1answer
30 views

Is continuous inputs an assumption of factor analysis?

Should we use only continuous inputs for factor analysis (FA)? My data is a mix of continuous and categorical inputs: one of the inputs has only 600, 700 and 1000 as values. I found that principal ...
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21 views

Factor Analysis

I have following data regarding Voice traffic(dependent variable) and some 10-12 other variables which are my independent variables. So, to use factor analysis shall I use voice traffic as one of the ...
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46 views

How is survey respondent segmentation based on market opportunity score done in practice?

As per instructions, I have administered a survey to a sample population that for several different "jobs-to-be-done" asks the survey participants to rate the importance of the "job-tobe-done" and the ...
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11 views

Component score covariance matrix [closed]

What does the component (factor) score covariance matrix in PCA or FA explain?
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1answer
50 views
+50

PCA/factor analysis of mixed (quantitative + qualitative) data: inconsistent results

I have a dataset composed of 4 variables, 2 being numerical and 2 categorical (ordinal in fact). They all represent 4 types of indicators/measures of the same phenomenon . I want to analyse them in a ...
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1answer
31 views

Is structural equation modeling (SEM) just another name of confirmatory factor analysis (CFA)?

I am reading some material about structural equation modeling. I found it to be extremely similar to confirmatory factor analysis - modeling a construct as the linear combination of several other ...
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14 views

Unexpected One-Factor in EFA

I have a data set of 4,000 participants. Each has rated 25 sentences on a scale of 1-100 (lowest amount of aggression present to highest amount of aggression present in each scenario portrayed in the ...
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0answers
18 views

Factor Analysis - Rotated Component Matrix Error

I haven't got good English but i have a problem: (for my master thesis.) I did factor analysis, deleted 4 questions and the most lower points are: ,392 and ,393. So, i go on and deleted 0,392 ...
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14 views

SPSS - Using K-means clustering after factor analysis [migrated]

I am a developer that has been tasked with working out how previous results using SPSS were gathered, so we can repeat the process with some new data. We can't ask the person who did the original ...
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0answers
15 views

Single factor solutions - EFA

I am exploring the properties of a 6-item self-report measure. I have about 155 cases and the items are completed on 7-point Likert scales. I have carried out an EFA, and extracted only one underlying ...
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0answers
10 views

Acceptable to use EFA when using binary data? [duplicate]

I'm working on my dissertation, and my committee has suggested I use Exploratory Factor Analysis to see if my findings conform to the results that previous researchers found after conducting a PCA. ...
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37 views

Is the use of PCA appropriate to validate a designed questionnaire?

I looked at the questions that may already have my answer but unfortunately it is not the case. I would like to ask again my question which has been revised to fit the rules. I am to measure 5 ...
2
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1answer
42 views

Rotation to get equal loadings in the first principal component or factor

I have the observations of $n$ variables $x_i(t)$ where $t$ is the time, and $i=1,2,\dots,n$ is the number of the variable. They're very correlated, so I wanted to use PCA. The first component ...
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0answers
9 views

analysis of responses to functional questionnaires in terms of improvement over time, comparing two randomised groups

We studied a population that was randomised into 2 treatment groups, evaluating answers to functional questionnaires at different time intervals (6 weeks, 3 months, 6 months, 1 year). Is it possible ...
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0answers
15 views

Can I ignore a single Item Factor and proceed with the remaining factors ? Is it scientifically correct?

I did an EFA and got 7 factors . There were a total of 54 items in the survey instrument. Now, the factors are in such a manner that Factors 1 to 6 have decent number of items loaded ( ranging from ...
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8 views

Co-variance matrix and Factor graph representation

I have problem in fundamental understanding of factor graph representation: I am trying understand the relation between the Co-variance matrix and associated factor graph, of a Normally distributed ...
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0answers
20 views

Factor analysis with 2-norm equality constraint

I'm interested in the interpretation of the solution to the factor analysis problem with a 2-norm equality constraint on the columns of the loadings matrix. I plan to decompose $\mathbf{X}_i \in ...
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12 views

Is the Kaiser–Meyer–Olkin measure of sampling adequacy relevant to CFA?

I often see the KMO mentioned in the context of exploratory factor analysis, but have never seen it mentioned in the context of confirmatory factor analysis. Is it appropriate for use in relation to ...
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2answers
74 views

Independent and Dependent variables use different scales

How to deal with questionnaire, where 40 questions that represent 8 independent constructs use 5-point Likert's scales and another 5 questions that represent dependent variable use 6-points Likert's ...
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57 views

Identifiability in factor analysis

Say we model $\mathbf{x}_t \in \mathbb{R}^d$ as a linear combination of factor loadings: $$\mathbf{x}_t = \mathbf{E}\mathbf{F}_t + \boldsymbol{\epsilon}_t, \qquad \boldsymbol{\epsilon}_t \sim ...
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0answers
13 views

Is sign of loading and score immaterial for interpretation in PCA & Factor Analysis? [duplicate]

Is sign of loading and score immaterial and can be ignored for interpretation? Or is there a important significance for sign when used to interpret the result? I am assuming sign can be ignored ...
7
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1answer
162 views

What is the intuitive reason behind doing rotations in Factor Analysis/PCA & how to select appropriate rotation?

My Questions What is the intuitive reason behind doing rotations of factors in factor analysis (or components in PCA)? My understanding is, if variables are almost equally loaded in the top ...
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15 views

What are the main differences between principal component analysis PCA and factor analysis [duplicate]

I have used PCA in my thesis and would like to argue (in best way) during viva the choice in addition to the fact that PCA analyses the variance of the observed items whereas FA analyses covariance.
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16 views

Create a 'biplot' (using factor analysis?) showing effect of each input variable on a two-output solution

I have a couple hundred datapoints, each of which has 6 input variables which run through a complex simulation to give two output variables. Because I have two output variables, I can create a nice ...
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0answers
14 views

How to quantify factor loadings in EFA?

Assume an example of EFA from Wikipedia. There are 1000 students, 10 academic fields and 2 factors found: "verbal intelligence" and "math intelligence" so every variable is loaded with these two ...
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18 views

What is the difference between principal component and maximum likelihood methods in exploratory factor analysis? [duplicate]

What is the difference between principal component and maximum likelihood methods in exploratory factor analysis?
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1answer
38 views

correlations between factors in r- scores or loadings?

I've conducted a factor analysis in r with three factors (function=fa {psych};rotation=promax ; method=GLS). ...
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13 views

Which CFA model is the best fit in my translation & validation study?

I have translated and adapted a questionnaire (based on a 5 factor model; 23 items) into my native language by following ITC and MAPI guidelines. Forward / backward translation, expert panel review, ...
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0answers
22 views

Comparing factor structure to network analysis using a community detection algorithm

I am interested in the use of weighted correlational network analysis to explore high dimensional data, instead of latent variable models like exploratory factor analysis (EFA). My approach is to: ...
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16 views

How to allocate questions to factors using R output?

I have the R output below, but don't know how to allocate questions to the factors. Any advice? ...
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1answer
57 views

Is Predicted R-squared a Valid Method for Rejecting Additional Explanatory Variables in a Model?

I'm building a model to understand the important drivers from a set of possible drivers for a time series of data. In my case the possible drivers are other time series. Like most statistical models ...
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0answers
18 views

First factor in Exploratory Factor Analysis and Principal Component Analysis

I am conducting an Exploratory Factor Analysis (EFA) and I was wondering if it is common or appropriate to say that the first factor is the strongest or most important of the model as it is explaining ...
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0answers
15 views

Finding MLE by factor analyzing the correlation matrix

In the book "Applied Multivariate Statistical Analysis" written by Johnson and Wichern, they have mentioned that the MLEs ($\hat{L_z}$) are obtained from the the correlation matrix $R$ by inserting ...
2
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1answer
36 views

Understanding a “computationally convenient uniqueness condition” on loadings in factor analysis

In "Applied Multivariate Statistical Analysis" by Johnson and Wichern, the authors mention a "computationally convenient uniqueness condition" $$L^T\psi^{-1}L=\Delta,$$ where $\Delta$ is a diagonal ...
0
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1answer
25 views

Is it possible to conduct confirmatory factor analysis in SPSS?

I found the factor analysis of SPSS seems to only support EFA, but I am not sure. Is it possible to conduct CFA in SPSS? If not, what statistical tool can be used to conduct CFA? I especially need ...
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27 views

Should I be concerned that the correlation between factors changes sharply when I move from EFA to CFA?

I am running an EFA and CFA on the same data (I realise this would not normally be appropriate). I've found that when I do an EFA (direct oblimin rotation) with a four-factor solution there is a ...
2
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1answer
82 views

Why confirmatory factor analysis has more degrees of freedom?

I am reading the textbook "Multivariate Data Analysis" and I am puzzled by one statement it makes about confirmatory factor analysis, saying that CFA has more degree of freedom than EFA. The following ...
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67 views

How to compute component or factor scores when the analysis is based on polychoric/tetrachoric correlations?

[This question is modified based on suggestion from @ttnphns] I am doing linear principal component analysis (PCA) based on polychoric correlations between the variables (rather than on native ...
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0answers
12 views

Tetrachoric Correlation Between Some Columns — R Factor Analysis Smoothing

My data has a number of columns that are dichotomous (in one case I seem to have a ternary logical relationship). I have been trying to perform exploratory factor analysis on this data. I can split up ...
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24 views

Matlab FACTORAN error on line 162: a covariance matrix is not positive definite [closed]

I have a data set called Z2 that consists of 717 observations (rows) which are described by 33 variables (columns). The data is standardized by using ZSCORES. Additionally, there is no case for which ...
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0answers
17 views

SEM design on dyadic data. Please help!

I have two surveys, and one is implemented to counselors. The questions ask about they feel about their relationship with their administrator. It has have two dimensions, let's say d1 and d2. I have ...
0
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1answer
69 views

What does “varimax” mean in SPSS factor analysis?

In the rotation options of SPSS Factor Analysis, there is a rotation method named "Varimax". If I choose this option, does it mean the same orthogonal rotation techniques of Principal Component ...
5
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1answer
78 views

Strange results in parallel analysis — weird output by rstudio but not R-Fiddle

Major UPDATE based on discussion with Aleksandr Blekh's answer (thanks so much!): This MRE would run with no problem in R-Fiddle ...
2
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1answer
45 views

Compute component scores from principal$loadings directly in R

I am using a polychoric correlation matrix to run PCA, so I cannot obtain the scores directly from the function. I am currently manually plugging in the numbers from the ...
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19 views

Finding redundant variables

I have data of several variables (all numeric or continuous) on different subjects. I want to find out if some of these variables are highly correlated so that not all need to be determined. This will ...
2
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1answer
47 views

factor analysis with missing values

I have data on about 25 subjects and 30 variables with about 20 missing values. The data is missing at random. What will be the best approach to perform factor analysis. How is factor analysis versus ...
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0answers
19 views

Does biplot() function in R use rotations or loadings to plot arrows? [duplicate]

For following code performing principal component analysis: ...
2
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1answer
31 views

How to use factor analysis / PCA / regression for data having serial IV and DV?

I have data regarding effect of a food chemical on blood and urine levels as well as effect on blood sugar and cholesterol. So I have following variables: ...
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How to determine proportion of variance explained in factor analysis

How can I determine proportion of variation explained by 2 factors obtained in output of following code of factor analysis using pacakge "rela" in R: ...