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===Kaiser's (1960) eigenvalue-greater-than-one rule (K1 or Kaiser criterion)===
Compute the eigenvalues for the correlation matrix and determine how many of these eigenvalues are greater than 1. This number is the number of factors to include in the model. A disadvantage of this procedure is that it is quite arbitrary (e.g., an eigenvalue of 1.01 is included whereas an eigenvalue of .99 is not). This procedure often leads to overfactoring and sometimes underfactoring. Therefore, this procedure should not be used.<ref name =Fabrigar /> A variation of the K1 criterion has been created to lessen the severity of the criterion's problems where a researcher calculates [[confidence interval]]s for each eigenvalue and retains only factors which have the entire confidence interval greater than 1.0.<ref>{{cite journal | last1 = Larsen | first1 = R. | last2 = Warne | first2 = R. T. | year = 2010 | title = Estimating confidence intervals for eigenvalues in exploratory factor analysis | url = | journal = Behavior Research Methods | volume = 42 | issue = 3| pages = 871–876 | doi = 10.3758/BRM.42.3.871 | pmid = 20805609 | doi-access = free }}</ref><ref>{{cite journal | last1 = Warne | first1 = R. T. | last2 = Larsen | first2 = R. | year = 2014 | title = Evaluating a proposed modification of the Guttman rule for determining the number of factors in an exploratory factor analysis | url = | journal = Psychological Test and Assessment Modeling | volume = 56 | issue = | pages = 104–123 }}</ref>
===Cattell's (1966) scree plot===
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