Die Invarianz oblique Faktoren unter Bedingungen zufälliger Daten wird als Funktion der Stichprobengröße (50, 100, 200), der Anzahl der Variablen (15, 30, 45) und der Anzahl der extrahierten Faktoren (5, 10) untersucht.

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Cite This Study

NESSELROADE et al. (Thu,) haben diese Frage untersucht.

synapsesocial.com/papers/6a125132a4bed3c7b166e829 https://doi.org/https://doi.org/10.1207/s15327906mbr0602_4

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1FACTOR ROTATION FOR PROPORTIONAL PROFILES: ANALYTICAL SOLUTION AND AN EXAMPLE1955 · 58 citations
2Statistics for Psychologists1966 · 1,898 citations
3The Use of Factor Models in Curriculum Evaluation: A Mathematical Model Relating two Factor Structures1967 · 13 citations
4Rotation to Achieve Factorial Invariance1964 · 168 citations
5On the oblique Rotation of a Factor Matrix to a Specified Pattern1969 · 24 citations

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1FACTOR ROTATION FOR PROPORTIONAL PROFILES: ANALYTICAL SOLUTION AND AN EXAMPLE1955 · 58 citations
2Statistics for Psychologists1966 · 1,898 citations
3The Use of Factor Models in Curriculum Evaluation: A Mathematical Model Relating two Factor Structures1967 · 13 citations
4Rotation to Achieve Factorial Invariance1964 · 168 citations
5On the oblique Rotation of a Factor Matrix to a Specified Pattern1969 · 24 citations

Bewertung der Faktorenskalierung im schiefen Raum: Basisdaten, die aus Zufallszahlen generiert wurden | Synapse