- Since all studies share the same true effect, it follows that the observed effect size varies from one study to the next only because of the random error inherent in each study. (Borenstein et al., 2009)
- Since all the indices are based on Q (in relation to df), it follows that all will be low (or zero) if the total dispersion is low relative to the error within studies, and higher if the total dispersion is high, relative to the error within studies. (Borenstein et al., 2009)
- If the inflation factor for the variance moves from 1.00 to 2.00, it follows that the inflation factor for the standard error (which is the square root of the variance) will move from 1.00 to 1.44. (Borenstein et al., 2009)
- This is because if the resources won by a focal individual in competition depend on its own genotype, it follows that they will also be influenced by the genotypes of competitors, giving rise to indirect genetic effects (IGEs; Moore et al 1997; Moore et al 2002) on resource acquisition and resource dependent traits. (Boulton et al., 2018)
- As the designation of focal and opponent individuals is in fact completely arbitrary for each observation x, it follows that focal and opponent effects should be perfectly correlated within individuals. (WILSON et al., 2011)
- If the focal individual is observed to win the contest, then it follows that the opponent must have lost. (WILSON et al., 2011)
- The following is an interesting quantity: 1 N i'x 1 N (x1, , xn ) 1 N n xi x i 1 is the mean of all xi From this, it follows that: n i'x = xi is the sum of all xi i 1 Similarly, let y denote another (N, 1) vector of data. (Werf, 2000)
- Under these assumptions, it follows that X *N (0,1) and T~W{1(1{K), where K is the disease frequency and W is the cumulative distribution function for a standard normal random variable. (Do et al., 2012)
- For example, it follows that PCA cannot be used to distinguish between models that lead to the same mean coalescence times (for example models with migration or isolation). (McVean, 2009)
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