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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In PCA, are PC scores the same as factor scores?

Are PC scores and factor scores the same thing? If so, are PC scores just the original but centered scores multiplied by the i-th eigenvector? Is the corresponding i-th eigenvalue the variance of ...
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2answers
27 views

Is CFA appropriate for test retest reliability?

I know CFA is often used when there is a latent variable that has measurement error that can attenuate correlations. However, does it make sense to make this same adjustment for measurement error when ...
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1answer
22 views

Algorithm to determine a point in time series data, after which probability of increase in value is very low

I am working with dataset which contains number of movie tickets sold per day. This is basically a count of total number of tickets sold, for a particular movie, for each day after its release date. I ...
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8 views

Index Creation using Ordinal Variables and Principal Components

I am creating an index based off 5 ordinal variables [coded 0,1,2,3]. I ran a Factor Analysis / PCA on the data and it shows that they all fit on a single factor, explaining ~50% of the variance. I do ...
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1answer
15 views

Likelihood Ratio Criterion in EFA

This is in ref to pp. 54-55 in McDonald,R.P[1] in the context of exploratory factor analysis (EFA) ML estimation. The likelihood ratio criteria, to me, seems to be performing dual roles: I. Providing ...
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134 views

Sum of rating scores vs estimated factor scores?

I'd be interested to receive suggestions about when to use "factor scores" over plain sum of scores when constructing scales. I.e. "Refined" over "non-refined" methods of scoring a factor. From ...
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14 views

Data sampling for EFA, CFA, SEM, and beyond

Assuming I split my dataset (n = 650), for the purpose of performing exploratory factor analysis on half of the data, and then confirming the extractor factor structure using confirmatory factor ...
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1answer
40 views

Meaning of “likelihood ratio criterion is distribution free”

This is in ref to pp. 54-55 in McDonald,R.P (1985) [1] in the context of exploratory factor analysis (EFA) estimation: I am confused as to the meaning of: "(the likelihood ratio criterion) is a ...
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1answer
28 views

what is the best approach for factor analysis when the data has more attributes than inputs? [closed]

i think i should ask the question like this: i am having a data set of 20 participants with 89 attributes , almost all of the attributes have values between 5 to 0 and there exist more than 20 ...
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9 views

different directions of the dimensions of multiple correspondance analysis

I have done a mca. My focus is about supplementary variable, that I want to see their behavior. This variable is significant (v.test) with the dimension 2 and 3. Both for the dimension 2 and dimension ...
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11 views

How to assess similarity of two sets of Principal Component Analysis loadings

A predictive model that I currently use relies on PCA with varimax rotation to reduce the dimensionality of the data (whether this is appropriate is a separate question). The dataset consists of ...
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1answer
58 views

Can lavaan (SEM/CFA) be used to do factor analysis like factanal (EFA)

I understand that lavaan is designed to do SEM/CFA while the R function factanal does EFA. EFA and CFA seem very very similar, ...
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1answer
18 views

Prediction of unknown triples for relational learning tasks using RESCAL

Background: I am focusing on a relational learning task, where links between entities are predicted across several relations. An example of a relation in this task is if two entities have the same ...
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1answer
46 views

Cross-loading opposite sign items in EFA

I've seen some similar questions to this, but nothing spot on so I thought I'd ask. I'm running an EFA with 54 items (and going with the 3 factor solution as it has the least cross-loadings and ...
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18 views

Factor Analysis in SPSS

After running the Factor Analysis in SPSS, the KMO and Bartllet's test shows that factor analysis is significant. However, the result has only one factor. IS it normal or having some mistake? And ...
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47 views

Setting up a MCMC scheme for Multivariate Stochastic Volatility

I want to understand the survey of Lopes and Polson (2010) regarding MV stochastic volatility. Assume the $p$-dimensional vector $y_t$ follows $$y_t\sim N(\Theta,\Sigma_t).$$ In order to model the ...
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2answers
23 views

Clustering of binary/nominal variables in one sample

Assume that a medical school classifies its active, full-time students according to their free time activities. By distributing simple questionnaires individuals have to answer whether or not they're ...
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1answer
29 views

Should I still need to use Factor Analyses for the scales used in previous papers?

Let's say, I used two scales that measures - 1. Perception of eco-label and 2. Perception of eco-brand. Each of them have 4 items (questions). Items are measured on 7 point-likert type questions. ...
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11 views

High residual reproduced correlations in factor analysis vs sample size

I am a Psychologystudent who had to execute a survey for her study. The criteria where that I had to have at least 25 people and that every scale would have at least 5 and maximum 10 items. My survey ...
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65 views

Rotation as conceptualization: what would be an intuitive illustration of varimax vs quartimax?

I am trying to find an intuitive illustration -- particular of varimaxand quartimax -- to inform the choice of rotation (in the ...
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1answer
90 views

What are dangers of calculating Pearson correlations (instead of polychoric ones) for binary variables in factor analysis?

I do research on educational games, and some of my current projects involve using data from BoardGameGeek (BGG) and VideoGameGeek (VGG) to examine relationships between design elements of games (i.e., ...
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1answer
58 views

Understanding factor correlations and factor score correlations in CFA and EFA

I've come across something a little puzzling when comparing factor scores estimated using EFA and CFA models, which I'm hoping someone here can explain to me. I have survey data featuring three sets ...
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114 views

Factor rotation methods (varimax, oblimin, etc.) - what do the names mean and what do the methods do?

Factor analysis has several rotation methods, such as varimax, quartimax, equamax, promax, oblimin, etc. I am unable to find any information that relates their names to their actual mathematical or ...
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1answer
39 views

The results of EFA are different from those of theory, how to conduct CFA?

I have a dependent construct (attitude) which has at least 2 dimensions in theory (affective & behavioral). The scale measure adopted for this research is found to have 2 or 3 dimensions in ...
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1answer
32 views

What is a good data reduction technique for nominal or dummy variable data?

I have a large data set with nominal and dummy variables. What's a good data reduction technique to use? Factor analysis cannot be used here, can it? Bonus points if there is an ...
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22 views

Full Factorial Experiment to figure out what drives website traffic, sanity check

So for my intro to statistics class assignment, I'm supposed to perform a full factorial experiment on a dataset that correlates Traffic, Keywords and a few other factors using multi-way anova and ...
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9 views

Negative Cronbach's alpha after reversing results of a survey

As part of my master thesis, I am conducting a PCA analysis. The analysis is aiming to find commonalities between 8 survey questions that were answered by 219 respondents. The survey was answered on a ...
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52 views

Interpreting factor loadings and calculating factor scores

How do I interpret factor loadings? A related question, I think, is how do I calculate factor scores? In these forums, I've read that factor score = sum of loadings times standardized item scores. ...
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28 views

EM bound for factor analysis, imaginary?

I am implementing factor analysis using EM. I get the likelihood, always increasing as expected. However, when I try to get the lower bound for which we have a closed form that allows us to keep ...
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1answer
87 views

Orthogonality of the basis in factor analysis

I have been studying principal component analysis (PCA) and then I have gone up to factor analysis (FA). I understood that PCA seeks orthonormal basis, but I am not so sure if this is the case for ...
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13 views

Confidence interval for difference of treatment means in unbalanced factorial design

Here is an example of a factorial design that is unbalanced. The factors are degree and gender with response as salary. I am trying to put a confidence interval around difference between treatment ...
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36 views

Interpretation of Principal Component Analysis Results

I have a 13-item, 5-point Likert-type scale that I have put together from similar questions used in the literature (n = 96). What is the best way to analyse my scale data? Step-by-step, what I have ...
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27 views

Bias in Factor Score Regression

I'm trying to understand the bias in factor score regression when factor scores are used as observed(independent) variables in regression analysis. I found one paper which talks about this bias. But ...
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14 views

What happens when I “flag” (set to 0) small loadings to compute factor / component scores?

In Q Methodology, it is common to logically flag (where FALSE sets the loading to 0) small or "insignificant" factor/component loadings before computing factor/component scores – prior to calculating ...
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95 views

Implementing Factor Structure Model

I'm trying to implement the factor structure model using Gauss Quadrature or MCMC method as done by many in their research work. The model is to find the effect of latent factors on response variable ...
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1answer
42 views

How to deal with categorical variable - location- with more than 60 levels

I am new to statistics and to categorical variables. I need to predict the cost based on several variables and it happened that all of my variables are categorical. I tried doing a linear regression ...
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20 views

Categorical Principal Components model summary

I have three questions on CATPCA using SPSS. 1) If I use a varimax rotation, it gives "Model Summary" and "Model Summary Rotation". Should I report values on the Model Summary Rotation since that was ...
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17 views

Calculate distances of a company branches from main branch in every state. How calculate distance for main branch in every state?

Suppose that I'm calculating distances of a company branches in every state from main branch of that state. After that I'm combining this feature with other features to creating a composite indicator ...
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1answer
19 views

How to measure quality of a split for numeric values?

I have a big set of real numbers. Each number comes with a list of associated attributes (some of them are numeric, others are categorical). For example, to make it less abstract, I have income of ...
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1answer
31 views

Same rotated component matrix in Factor Analysis despite using different normalizations

I'm using SPSS for factor analysis with these options: ...
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9 views

what techniques can be used to model the covariance matrix?

I have a covariance matrix with n variables. I am interested in learning how these variables may interact. For example some questions I am interested in are: causality: which variables in yi..k ...
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1answer
19 views

Cluster analysis? Factor analysis? Classification? What's the procedure to group students into profiles based on elective course enrollments?

I am trying to find the right statistical procedure to use to analyze a set of course enrollment data for students. The enrollment data is binary (0/1) for a large number of a group of students. I ...
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27 views

regression with factors (from factor analysis)

I have n=100 and measures =500. Using dimensionality reduction, I want to contruct latent variables with 500 variables and test each factors in an anova model.What is the nest approach to create ...
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1answer
45 views

Is it possible to normalize data by different group leaders separately?

I have a dataset that contains different states of a country. In every state there are different companies and one company in every state is manager of other companies in that state (other companies ...
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13 views

problem in factor analyzing

i am having problem with my data. i am doing a research and my data is a real data that means the meaning of my data is important, i am trying to run factor analyzing on my data set to minimize the ...
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1answer
23 views

Exploratory Factor Analysis will not converge

I'm new to SEM, so I wanted to learn how to do an exploratory factor analysis before moving on to SEM. I am trying to model metabolic data ...
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1answer
64 views

Calculate thresholds of factor analysis output to classify data to 5 classes

Suppose that we calculate a composite indicator for some companies using Factor Analysis (FA) by combining five features to one output (calculate weights of input features). This is histogram of ...
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1answer
54 views

How to justify the choice of independent variables in multiple regression

I am trying to measure the effect of atmospheric factors as smell or light (IV) on purchase behavior (DV). In total I have xx likert scales that contain 5 likert items and responses are coded from 1 ...
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14 views

Repeated measures ANOVA

I am attempting to explain results for my dissertation and am stumped at how to interpret this. The premise is that individuals who had executive coaching experiences reported their coaching goals ...
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1answer
40 views

Reduction of questionnaire via FA versus control group

We are developing a questionnaire for evaluation of burden of disease after certain medical conditions. The questions are developed partly from semistructured interviews. My statistician argues for ...