Factor analysis is a dimensionality reduction latent variable 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 ...

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Post-hoc for 2x2 mixed design ANOVA using SPSS with two dependent variables

I am analyzing an experiment run with 162 participants using a 2×2 mixed design ANOVA. The experiment has two independent variable with two levels each, and two dependent variables. I need to know ...
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62 views

Combining two variables

I have a questionnaire about factors that affect trust in online shopping. The questionnaire is split into 5 topics (such as security, privacy, website design etc.) with 2 questions per factor. I've ...
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Getting estimate and CI for dummy variable in linear model

I have a linear model based on some variables (age, gaming and tasks) on response time. It looks like this: ...
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orthogonal latent trend

Assume I have 2 explanatory variables (or factors) X which explain y. I want to extract a trend (and maybe seasonality) from y which is/are orthogonal to X. Is there are a way to do this? Can PLS do ...
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Matrix Factorization in Recommender Systems: Uniqueness of SVD?

I was studying the collaborative filtering approach about recommender system and I read about matrix factorization approach. In SVD version, I have not figured out how the non-uniqueness of the ...
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19 views

The unique variance in Factor analysis

This might be a rather simple question, but this is troubling me a lot? Please help. Suppose in a factor analysis model, there are three variables $x_1$, $x_2$ and $x_3$, and two latent factors ...
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Factor Analysis only one Eigen Value above 1

I'm doing a study for HR about a certain company's interviewing style. A number of respondents were given a 7 level likert scale (1 strongly disagree, 7 agree), and I need to find out whether I can ...
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15 views

How to obtain new variables using factor analysis in R?

I am working with 8 variables that are correlated with each other, and want to use factor analysis to construct two factors and then use them in my regression analysis. I typed this in R: ...
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Reading Centroid extracted factor matrix into SPSS for rotation, analysis [migrated]

I've been struggling with this for the last 4 days. I have concluded that I'm not smart enough to sort this out on my own, and I want to do this right. Desired Outcome: I want to instruct SPSS to ...
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Question: next step after regression analysis? how to tell if multiple variables all co-correlate?

I am new to regression analysis and I have found that my 'independent variable' or predictor correlates with several dependent variables (through multiple linear regression tests) in a way that ...
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27 views

Factor analysis in Market Research

I am doing a survey to find out customer experience/satisfaction for a specific product. My survey contains a scaling question in which i asked satisfaction level (from 1 to 5) 5 being very ...
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14 views

Reproducing statistical experiment

I've conducted a survey to test a model where I have one dependent variable and multiple independent variables. These variables are assessed using multiple items. The items I used are obtained from ...
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25 views

Factor Analysis on items measured on two different 5 likert scale items that is one scale is measuring frequency and other the agreement

Can I run factor analysis on items that are measured on two different 5 likert scale, that is one scale is measuring frequency ( i.e never , rarely, occasionally, frequently and always) and other ...
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24 views

Eigenvalues for Factor Model

Suppose that I have a 10 factor factor model. There is a eigenvalue associated to each of the 10 factors. How do I calculate these eigenvalues?
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Correlation Matrix from given R output of Factor Analysis

I carried out a factor analysis of 5 variables using a single factor. How do I estimate the correlation matrix assuming the one factor model holds? The R output is:
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How to calculate factor scores for variables in different scales?

I have 7 variables that reduced to 3 factors using both the factanal and psych packages in R. I would like to use these 3 ...
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In factor analysis what is more stable sample to sample: regression coeffients or structural coefficients?

In Which matrix should be interpreted in factor analysis: pattern matrix or structure matrix? ttnphns remarks "Weak side of pattern matrix is that it is less stable from sample to sample (as usually ...
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20 views

PCA + Parallel Analysis

When I realize the Factor Analysis (I have 16 items), the PCA says I have 5 factors. But in the scree plot there is no elbow at all, just a decreasing line, that makes me think maybe I shouldn't be ...
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22 views

Calculating Eigenvalues in Factor Analysis and Calculating Factor Loads

So, as I wade back into the world of stats, I am finding myself confused about a few things when it comes to Factor Analysis. So I understand the bits about calculating Eigenvalues from a Correlation ...
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Will CFA produce the same loadings as an obliquely rotated EFA under these conditions?

I have in mind figures like the following, which purport to explain the difference between EFA (left) and a 'standard' CFA (right). I guess in this picture one loading per factor should be fixed, and ...
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Identification in confirmatory factor analysis

Consider a factor analysis $x_{ik} = a_{i} f_k + u_{ik}$. Usually, this model is estimated with identification restriction, say, with the first component of $f_t$ being one. This is to address the ...
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36 views

PCA on a Likert scale data

I am trying to conduct a small experiment based on Likert style data. I have a total of 20 questions, 10 are referring to a latent construct of happiness, and the other 10 to a latent construct of ...
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29 views

Factor loading of predictor on outcome variable

I know the basic and some more advanced statistics. I want to use multiple lineair regression to see whether the standardized questionnaire PsyCap, leader adaptivity and employability culture can ...
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42 views

What is an intuitive definition/explanation of an intercept in SEM?

Some of my friends/colleagues have recently taken an interest in structural equation modelling, and I have been having to field an increasing number of questions about SEM. Often times, these ...
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Factor analysis Geometric interpretation of common variance [duplicate]

I am trying to understand the fundamental differences between PCA and Factor Analysis. PCA is straight forward in that you take the eigenvectors of the data's variance (and hence considering all the ...
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What's the relationship between initial eigenvalues and sums of squared loadings in factor analysis?

On the one hand I read in a comment here that: You can't speak of "eigenvalues" after rotation, even orthogonal rotation. Perhaps you mean sum of squared loadings for a principal component, ...
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EFA: interpreting negative factor loadings [duplicate]

I've run an exploratory factor analysis with oblique rotation, and specifying three factors. The first two factors are correlated at almost zero with one another, while there's a negative correlation ...
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Which Method of Factor Extraction is Preferable With Communality Greater than 1.0?

I am trying to perform Exploratory Factor Analysis using SAS's proc factor with priors=smc, but am not sure which factor ...
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What kind of multivariate data is this judging from the QQ plot and Scatterplot Matrix?

This dataset is from R "cluster.datasets" package, named life.expectancy.1971. I would like to run Maximin Likelihood EFA(Exploratory Factor Analysis ) and therefore I checked the Multivariate ...
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How to tell if the survey is good enough/valid?

I just used 15-items questionnaires X which has never been used in my culture C. I've found that in my sample (n=150) α = .77, principal component analysis with 5 factors more than 1 eigenvalue, ...
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26 views

Bootstrapping data for factor analysis

How can I bootstrap my data before doing factor analysis?
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How to determine which factor rotation gives the best model fit? [duplicate]

I have to use factor analysis to determine if it fits my data adequately. I am wondering how rotations play into it. What am I looking for when I change the rotation? The p-value is the same so how I ...
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Factor rotations in non-negative matrix factorization?

My understanding is that solutions from Non-Negative Matrix Factorization (NMF) are not necessarily unique, and rotations can be imposed during the optimization process or after the solutions have ...
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26 views

We should normalize (or standardize) data before feature selection tests (t-test, related matrix, etc.)?

We should normalize (or standardize) data before these feature selection techniques? Which one for every technique? normalization of standardization? t-test Related matrix Stepwise PCA Factor ...
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51 views

How to use principal components as predictors in regression?

I have a couple of questions involving doing a regression (logistic or linear) after principal component analysis. If I find principal components using Principal component analysis, can I use these ...
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Multiple imputation and factor analyses

I have conducted a survey to collect my thesis data. The data naturally contains some missing values. I want to use multiple imputation but as I want to do a factor analysis this seems a little ...
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Model with factor scores as variables vs original?

I am new to this so please bear with me. I have two models, an original one with many variables, and a new one where I extracted 5 factors. I used both for a cox regression, and the model in which I ...
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32 views

Ranking questions based on how many participants answered “yes”

I have some data from a survey. In one question of the survey, participants were asked to choose one of nine objects from a given list. They then answered several "yes" and "no" questions about that ...
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41 views

Correspondence analysis: how are row principal and supplement coordinates calculated?

How are row principal and supplement coordinates calculated in correspondence analysis (CA)? Specifically, I am looking for a simple example as how to derive them using linear combinations of the row ...
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8 views

How to find the coefficient of parameters of shape and scale parameters of weibull distribution in Novel Energy pattern factor method?

Novel energy pattern factor method for Weibull distribution Please have a look on the paper for the further clarification of the question . Please help me out for finding out the coefficient of ...
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27 views

Why would an item loading have a negative sign while correlating positiviely with other items on that factor?

I've conducted an oblique EFA on 12 6-point Likert-type attitude measurement items from a scale I'm developing. I'm struggling to understand, however, why some of my variables are loading negatively ...
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Can SVD be used to perform factor analyis?

What is the relationship between SVD and factor analysis? How can use singular values and other matrices from SVD to perform factor analysis or cluster document-term matrix without using other ...
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22 views

Clustering based on SVD

I have a document-term matrix and I performed SVD on it. How can I cluster terms based on the singular values? Is there any relationship between SVD and factor analysis?
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27 views

EFA SPSS and Cronbach's Alpha

I have done the EFA in SPSS for my questionnaires and found 4 factors. Now should I use this EFA result to compute the Cronbach's Alpha, and if so then how to do that? Or Cronbach's Alpha is done ...
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Regularization methods for factor analysis (in the $n<p$ situation)

Is there any covariance matrix regularization suitable for factor analysis? I have a data matrix where number of observations is smaller than the number of dimensions: $n<p$. I am thinking of ...
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Respondent supplementary points from correspondence analysis using ca package in R?

I am new to correspondence analysis and I'm trying to decipher a paper's application of it. The authors surveyed 100 consumers on attributes that they would assign to different deodorant brands. The ...
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45 views

Why is covariance matrix not positive-definite when number of observations is less than number of dimensions?

I have a data matrix $X$ of size $n\times p$ with $n < p$, where $n$ is the number of observations and $p$ is the number of dimensions. My question is: why $n < p$ results in not a ...
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32 views

Testing linearity on SPSS (non-graphic)

I am conducting a study based on the technique of factor analysis. I am trying first to test the assumptions. One of the assumption which I am trying to test is the linearity between variables. Other ...
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30 views

Can I use factor analysis for data with scores between 0 and 1?

I have 20 items which I expect to be grouped into 4 factors (index). The scores for the items lie between 0 and 1. Can I use a factor analysis to reduce the 20 items into few factors? Then I should be ...
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Classification with multiple sets of data

Suppose there is the problem of finding what types of users on your site will take what type of action on some of your products. Actions being, buying, rating, downvoting, etc. Given a data set of ...