coefficient of determination

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coefficient of determination

[¦kō·ə′fish·ənt əv di‚tər·mə′nā·shən]
(statistics)
A statistic which indicates the strength of fit between two variables implied by a particular value of the sample correlation coefficient r. Designated by r 2.
References in periodicals archive ?
Table 3 Squared Multiple Correlations: (Group number 1 - Default model)
Shieh (2013) is highly critical of Equation 1, claiming that it is insufficiently accurate and that only computationally intensive simulation-based computer programs should be used to determine sample size requirements for the squared multiple correlation coefficient.
SQUARED MULTIPLE CORRELATIONS (INITIAL) Estimate leadership 0 culture 0 commitment 0.089 comm6 0.928 cult9 -0.345 comm12 0.165 lead22 0.996 lead5 0.772 org outcomes 0.768 comm7 0.351 comm4 0.274 cult11 0.352 cult1 0.717 lead15 0.902 lead10 0.785 TABLE 10.
Reliability: Cronbach's alpha and squared multiple correlations. Although Cronbach's alpha coefficient is the most commonly used reliability coefficient, a drawback is it makes no allowances for correlated errors of similar measures or the effects of more than one latent variable on any observed variable (Bollen, 1989).
In view of the importance of accurate sample size formulas for a precise confidence interval of the squared multiple correlation coefficient and computational demands of the current methods, Bonett and Wright (2011) proposed a simple procedure of approximating the sample size requirement for obtaining a squared multiple correlation confidence interval with desired precision.
Squared multiple correlations showed that significant variables explained enjoyment, 83% for boys and 82% for girls.
The differences identified in the relationships of the two models show that the squared multiple correlations in both cases are also different, while, in the current study, with exception of Membership, all of the variables of the model present values less than .50.
Moreover, the squared multiple correlations also indicate that EI-B1 has greater predictable power of the canonical correlation.
Data were analyzed using AMOS 4.0 to obtain regression weights, standardized regression weights, squared multiple correlations for the endogenous variables, and significance levels for test statistics.
Significant squared multiple correlations determined the criterion validity of the instrument.
In Figure 1, the squared multiple correlations ([R.sup.2]) predicting wellness from the three exogenous constructs, ethnic identity, acculturation, and mattering were spirituality = .07, self-direction = .85, schoolwork = .80, leisure = .43, love = .59, and friendship = .84.
Finally, LISREL estimates of item loadings, standard errors, and squared multiple correlations were also inspected for appropriate sign and magnitude (Bollen, 1989).