Variation in carotenoids, tocols, and microelements in parents and derived introgression lines was analyzed by one-way analysis of variance and the general standard error was used in the t-test to calculate the significance of differences among lines and parents.
In general, the standard errors across replicates were small.
In general, the standard errors for subsample IV estimates are larger when the effect size is larger, and standard errors decrease as n X increases.
It can be shown that, in general, the standard errors of empirical centiles are larger than those for the centiles calculated using the normal distribution.
Note that IV estimators in general have larger standard errors than the corresponding OLS estimators; in fact, the standard errors in the last two columns in Table 6 are much larger than those in the first two columns.
Both had the effect, in general, of increasing standard errors and p-values for the coefficient estimates as expected.
In general, much higher standard errors were found for solutions obtained for expression results of cathelicidins' than for defensins' genes.
In addition, we also develop a general procedure to construct standard errors for estimates of skill-mismatch derived from surveys like PIAAC, where the sampling frames can differ substantially across countries and where the test scores are derived from imputation models.
However, given the high standard errors, in general differences between accuracies obtained from different PE for a given trait were not statistically significant.
Data Cloning (DC), which was proposed by Lele et al. [ 24], is a computing algorithm to obtain maximum likelihood estimates (MLE) and their standard errors for general hierarchical models.
