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Questions tagged [parallel-analysis]

Parallel analysis is a criterion used to help decide the number of principal components or principal factors/common factors to retain. It is based on retaining eigenvalues of observed data greater than those corresponding mean eigenvalues from many data sets of uncorrelated data with the same $n$ observations and $p$ variables as the observed data.

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What statistical techniques can I use to model improvement over time?

Say you have a group of 30 students and you measure each individual's performance on a test at 4 intervals throughout the year. (For the purpose of this investigation, assume the tests taken are ...
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Parallel analysis for exploratory factor analysis

The suggested number of factors is 2, which is not consistent with my understanding of parallel analysis. In my view, we should keep factors which the eigenvalue of the factor is larger than that of ...
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Parallel analysis for principle components analysis and Multi-dimensional scaling

Does the same method for conducting a parallel analysis for principal component analyses apply to find the cut-off point for multidimensional scaling? Under the pretense that PCA and linear MDS are ...
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Adding interaction term to multivariate parallel growth model nlme/lme4

I've been using examples from Grimm, Ram, and Estabrook (2017) to construct a parallel multivariate model to explore the relationship across time between two continuous variables, FS and Left_dlPFC. ...
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Do the criteria for factor retention apply equally to component retention?

I'm familiar with aspects of the received wisdom about the selection of the number of factors in factor analysis. For example, Wikipedia suggests that Horn's parallel analysis is a good method, and ...
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25 views

Parallel analysis with rotated data

I am trying to do Factor analysis with varimax rotation for my data using R psych package. To determine number of factors I use R paran package. The problem I see is that eigenvalues produced by ...
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434 views

Unexpected eigenvalues in parallel analysis for factor analysis in SPSS

Would greatly appreciate if someone could clarify which eigenvalues I am supposed to compare when using parallel analysis to determine factor retention. I am running Principal Axis Factoring in SPSS ...
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473 views

Choosing how many factors to retain based on parallel analysis and on a scree plot without an elbow

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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How do random data eigenvalues change, as random variables are added?

I am using parallel analysis (Horn 1965) to determine how many principal components I can extract from my data. I can add more variables to my dataset, but I cannot add more cases (I know, that's ...
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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 ...
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How to correctly interpret a parallel analysis in exploratory factor analysis?

Some scientific papers report results of parallel analysis of principal axis factor analysis in a way inconsistent with my understanding of the methodology. What am I missing? Am I wrong or are they. ...
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545 views

Permutation test for factor analysis

We have a survey instrument and are interested in assessing dimensionality of it. Looking at plots of multidimensional scaling, it appears as though there are, perhaps, 3 distinct dimensions to the ...
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Can I do parallel analysis with any type of exploratory factor analysis/principal component analysis?

I wish to perform parallel analysis to determine how many factors I should extract from my maximum likelihood exploratory factor analysis. I have been referred to a program that calculates the ...
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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: ...
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Problem with parallel analysis with psych

I have a data set with several hundred variables and some thousand records. I'm reviewing the different ways for running a Principal Component Analysis and choosing the principal components. First I ...