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Can you use PCA on ordinal variables?
Also known as PCA/FA performed on tetrachoric (for binary data) or polychoric (for ordinal data) correlations. Normal distribution is assumed for the underlying (then binned) continuous variable for every manifest variable. Then classic FA is applied to analyze the aforesaid correlations.
What is polychoric PCA?
Polychoric Correlations That alternative is to base the PCA on a different type of correlations: polychoric. Polychoric correlations assume the variables are ordered measurements of an underlying continuum. They are interpreted the same way as Pearson correlations.
What types of research can use factor analysis?
There are mainly three types of factor analysis that are used for different kinds of market research and analysis.
- Exploratory factor analysis.
- Confirmatory factor analysis.
- Structural equation modeling.
Can a Likert scale be used in a factor analysis?
A very common question is whether it is legitimate to use Likert scale data in parametric statistical procedures that require interval data, such as Linear Regression, ANOVA, and Factor Analysis. A typical Likert scale item has 5 to 11 points that indicate the degree of agreement with a statement, such as 1=Strongly Agree to 5=Strongly Disagree.
Can you find true parameter values with Likert scale data?
For example, Lubke & Muthen (2004) found that it is possible to find true parameter values in factor analysis with Likert scale data, if assumptions about skewness, number of categories, etc., were met. Likewise, Glass et al. (1972) found that F tests in ANOVA could return accurate p-values on Likert items under certain conditions.
Do you need scale level data for factor analysis?
Traditional (linear) PCA and Factor analysis require scale-level (interval or ratio) data. Often likert-type rating data are assumed to be scale-level, because such data are easier to analyze. And the decision is sometimes warranted statistically, especially when the number of ordered categories is greater than 5 or 6.
Is there factor analysis or PCA for ordinal or binary data?
CatPCA accepts also nominal variables and any mixture of variable types (nice). Inferred underlying variableapproach. Also known as PCA/FA performed on tetrachoric(for binary data) or polychoric(for ordinal data) correlations.