1988
DOI: 10.1037/0033-2909.103.2.265
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Relation of sample size to the stability of component patterns.

Abstract: A variety of rules have been suggested for determining the sample size required to produce a stable solution when performing a factor or component analysis. The most popular rules suggest that sample size be determined as a function of the number of variables. These rules, however, lack both empirical support and a theoretical rationale. We used a Monte Carlo procedure to systematically vary sample size, number of variables, number of components, and component saturation (i.e., the magnitude of the correlation… Show more

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Cited by 2,215 publications
(1,527 citation statements)
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References 40 publications
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“…Although the current study tested a relatively small sample (N = 66), the results met both of the empirical stability criteria (Guadagnoli and Velicer, 1988), which supports generalizability of the dichotomous IA and PM factors to the larger population of adolescents with CD. The component saturation and stability index scores provide an empirical test of interpretability of factors for a given sample size, which has been shown to be superior to the traditional theoretical rules for determining adequate sample size (e.g., ratio of sample size to the number of factor items; Guadagnoli and Velicer, 1988). Based on these criteria, the factor structure resulting from the principal components analyses is interpretable for our sample size.…”
Section: Discussionsupporting
confidence: 62%
See 1 more Smart Citation
“…Although the current study tested a relatively small sample (N = 66), the results met both of the empirical stability criteria (Guadagnoli and Velicer, 1988), which supports generalizability of the dichotomous IA and PM factors to the larger population of adolescents with CD. The component saturation and stability index scores provide an empirical test of interpretability of factors for a given sample size, which has been shown to be superior to the traditional theoretical rules for determining adequate sample size (e.g., ratio of sample size to the number of factor items; Guadagnoli and Velicer, 1988). Based on these criteria, the factor structure resulting from the principal components analyses is interpretable for our sample size.…”
Section: Discussionsupporting
confidence: 62%
“…Guadagnoli and Velicer (1988) proposed a system for empirically testing whether factors found within a sample are stable and therefore interpretable with regard to the population. In this system, interpretability of the factors, referred to as stability, can be demonstrated by either of two comparisons: (1) component saturation; or (2) a stability index score.…”
Section: Sample Size and Pcamentioning
confidence: 99%
“…Again, all subscales demonstrated good internal consistency. Although the cognitive and behavioural avoidance subscales consisted of only three items each, both had good internal consistency and all of the corresponding items loaded above .6, suggesting that both are stable factors (Guadagnoli & Velicer, 1988; Osborne & Costello, 2009). We found that maladaptive support components, including trauma-specific maladaptive support (i.e.…”
Section: Discussionmentioning
confidence: 99%
“…In this study, ten edumetric items and 23 psychometric items were piloted using Guadagnoli's recommendation of approximately 150 respondents for stable factor analysis (Guadagnoli and Velicer 1988).…”
Section: Sample Sizementioning
confidence: 99%