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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Back end processing of Pattern Matrix during EFA. [on hold]

I want to know that how pattern matrix (using maximum likelihood and varimax rotation) is calculated. What is the underlying formula or pattern that displays such results? Please guide.
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20 views

Understanding contradictory results between screeplot (EFA) and CFA

I got some contradictory results. How can one explain that a screeplot and EFA clearly suggest a one-factor solution whereas several model fit parameters of CFA are in favor of a five-factor solution? ...
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42 views

Can I create an Index score using factor scores as weights?

I am creating an Overall Customer Satisfaction Index score based off of 4 factors that comprise satisfaction for callers to a call center: A representatives concern for your needs; ease of navigating ...
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1answer
16 views

If two domains measure the same thing how to approach a cluster analysis?

I would like to perform a cluster analysis on my sample with a set of variables categorized in several domains. This is just fine but my problem is that two domains (one consisting of four and one of ...
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24 views

Factor Analysis of Count Data

I am new to factor analysis. I inherited a project at work from another team. They took 9 variables that are all Poisson-distributed count random variables and ran a "regular" factor analysis in ...
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1answer
22 views

What type of analysis will help discover common attributes of collections of items?

Suppose the following situation. You have a list of food items: bottles of milk, ham pieces, eggs, bananas etc. You also have bags of food, where a bag might contain, e.g. 3 bottles of milk, 5 pieces ...
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34 views

Non-negative matrix factorization in recommender systems

As i understand, in NMF we should have our three matrices elements non-negative. But i can't understand how to do it so far. Shouldn't we just initialize our factor matrices at the start with random ...
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56 views

What is the rationale behind the “eigenvalue > 1” criterion in factor analysis or PCA?

What is the meaning of "eigenvalue > 1" criterion? I understand what eigenvalues and eigenvectors are. This question is w.r.t. this link and this statement there: By default, VARCLUS stops ...
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18 views

What will be application in my research - EFA or CFA?

I am trying to construct a model of factors affecting investment behavior where I have identified the factors from different literature (each factor from different research papers which say that the ...
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1answer
14 views

measure development - removing items from an item pool due to ceiling effect

During the early stages of scale development, many items within our item pool were found to have a strong ceiling effect with low score variability. In order to attempt create a meaningful measure ...
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21 views

How to construct a composite measure using several items in SPSS?

For my master thesis, I have to do a regression analysis. But, as an independent variable, I have to construct a composite measure, being perceived importance (of interest groups). I have 9 variables ...
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18 views

Factor scores for EFA with binary data

I am conducting an exploratory study which investigates goal progress predictors. The list of potential predictors is long (42) and I am attempting to reduce the number of predictors using factor ...
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40 views

Estimating static factor model for h-step ahead forecasting (using R)

I am trying to estimate a static factor model of the following form $$y_{t+1} = \beta'F_t+\gamma(L)y_t+\epsilon_{t+1}, \\ X_t=\Lambda F_t+e_t$$ where $F_t=(f'_t,...,f'_{t-q})'$ is $r\times 1$, where ...
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22 views

Should I exclude factors loaded by only one variable when computing factor score

I'm writing a thesis on "Factor affecting students academic performance at second cycle institutions." I used factor analysis to extract 20 factors from 63 variables that presumably influence ...
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3answers
72 views

“Two stage” factor Analysis: factoring saved factor scores

I have a model which consists of 19 questions, which are divided in three factors (factor 1 - nine questions, factor 2 - six questions, factor 3 - four questions). For this I did a factor analysis and ...
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240 views

Very different results of principal component analysis in SPSS and Stata after rotation

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
37 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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29 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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1answer
82 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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1answer
90 views

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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41 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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16 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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30 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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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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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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42 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 ...
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63 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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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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22 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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10 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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25 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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25 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
108 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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60 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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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 ...
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208 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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25 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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17 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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19 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
47 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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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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36 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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17 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
83 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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20 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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18 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 ...
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1answer
38 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 ...
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1answer
31 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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31 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 ...