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English: Figure 2 represents what researchers would be testing in Figure 1 but without standardized values and with fewer items for simplicity. Because intelligence and academic performance are merely imagined or theory-postulated variables, their precise scale values are unknown, though the model specifies that each latent variable’s values must fall somewhere along the observable scale possessed by one of the indicators. The 1.0 effect connecting a latent to an indicator specifies that each real unit increase or decrease in the latent variable’s value results in a corresponding unit increase or decrease in the indicator’s value. It is hoped a good indicator has been chosen for each latent, but the 1.0 values do not signal perfect measurement because this model also postulates that there are other unspecified entities causally impacting the observed indicator measurements, thereby introducing measurement error. This model postulates that separate measurement errors influence each of the two indicators of latent intelligence, and each indicator of latent achievement. The unlabeled arrow pointing to academic performance acknowledges that things other than intelligence can also influence academic performance.
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Author Nbreznau

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16 August 2022

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current06:32, 16 August 2022Thumbnail for version as of 06:32, 16 August 20221,980 × 1,155 (106 KB)NbreznauUploaded while editing "Structural equation modeling" on en.wikipedia.org

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