Scree plot
Diagnostic plot in multivariate statistics
In multivariate statistics, a scree plot is a line plot of the eigenvalues of factors or principal components in an analysis. The scree plot is used to determine the number of factors to retain in an exploratory factor analysis (FA) or principal components to keep in a principal component analysis (PCA). The procedure of finding statistically significant factors or components using a scree plot is also known as a scree test. Raymond B. Cattell introduced the scree plot in 1966.
A scree plot always displays the eigenvalues in a downward curve, ordering the eigenvalues from largest to smallest. According to the scree test, the "elbow" of the graph where the eigenvalues seem to level off is found, and factors or components to the left of this point should be retained as significant.
As the "elbow" point has been defined as point of maximum curvature, this property has led to the creation of the Kneedle algorithm.
01Etymology
The scree plot is named after the elbow's resemblance to a scree in nature.
02Criticism
This test is sometimes criticized for its subjectivity. Scree plots can have multiple "elbows" that make it difficult to know the correct number of factors or components to retain, making the test unreliable. There is also no standard for the scaling of the x and y axes, which means that different statistical programs can produce different plots from the same data.
The test has also been criticized for producing too few factors or components for factor retention.
Sources and credits
This article is adapted from the Wikipedia article “Scree plot”, written by its contributors and licensed under CC BY-SA 4.0. Fathomly has changed the layout, removed citation markers, navigation and maintenance notices, and adjusted punctuation. This adapted version is shared under the same license. For references, see the original article.
Images, from Wikimedia Commons:
- Screeplotr.png by Staticshakedown, CC BY-SA 4.0
- Yamnuska bottom cliff.jpg by Kevin Lenz (talk · contribs), CC BY-SA 2.5
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