The dramatic difference between these two agreement statistics for competition suggests that sample size is contributing to these patterns, as we discuss in Training Sample Sizes and Scoring Success.
Although these data are useful in comparing the incidence of cancers between countries, statistics for haematological malignancies are estimated by general categories such as 'leukaemia,' which includes all leukaemic diseases (Ferlay et al, 2010).
For comparison across schemes, allowing for correlation between them, we calculated differences between the C statistics for each paired comparison from every bootstrapped sample.
However, the current organization of the Results section causes the reader to constantly switch back and forth between statistics for grand-averaged data and for individual infant data.
The lower bound δ* depends on the correlation between the test statistics for H1 and H2.
Not surprisingly, the resulting orthologous gene data set further decreased the disparity between the summary statistics for each species (table 2, fig. 3).
In terms of agreement between the four statistics for individual items not exhibiting misfit it can be seen from Table 1 that, for instance for HADS-A, the infit and outfit means squares agreed with their equivalent t-statistic on 5 items for the Rating Scale Model; similarly there was agreement between the fit statistics for 4 items from the HADS-D.
We demonstrate in our experiments that the correlation between the marginal statistics for any two variants which are corrected for population structure is the same as the correlation of a transformed version of genotype for the same two variants.
Thus, we can re-write the covariance between the computed statistics for two SNPs as follow: Cov (S i, S c ) = Cov (X i ′, X c ′ ) = Cov (L X i, L X c ) This indicates that the covariance between the two marginal statistics corrected for population structure follows an MVN where the correlation between the two statistics is the correlation between the transformed genotype for both SNPs.
Of course, there is wide variation between individual labs for these statistics.
