Group differences were statistically analyzed using Student's t-test or One-way analysis of variance for unpaired values, Mann-Whitney's U test was used to analyze the metastases in liver, Kruskal-Wallis test for the ratio of liver to body weight, and Correlation of the CA19-9 and CEA content in serum with the liver metastasis was evaluated by Linear Regression test.
Statistical analysis was performed by soft program Graphpad Prism 5. Since the groups in comparison were independent of each other, and the values showed non-normal distribution, the significance of the differences between different groups were evaluated by Mann Whitney test, whereas the correlation was analysed by linear regression test.
Step 2: Ranking SNPs by linear regression: Second, we rank the SNPs by a linear regression test statistic.
We attempted to measure publication bias that is, a lack of small studies without significant results—by the linear regression test for funnel plot asymmetry described by Egger et al. (1997).
A linear dependence of crown and shoot system BEFs on TH was detected by the linear regression test and Pearson's correlation coefficient test of significance.
The dependence of component BEFs (taproots, lateral roots, and foliage) on DBH detected by the linear regression test and Pearson's correlation coefficient test of significance were also detected by the dcov test of independence; suggesting that, the most pronounced dependence of these component BEFs on DBH is linear, since dcov test measures all types of dependence (linear and nonlinear).
Age and postmortem delay did not affect the volume of the cholinergic interneurons, as was demonstrated by the linear regression test.
The prediction of skGFR from structural parameters was analysed by a linear regression test.
As only seven studies were included in the meta-analysis, assessment of publication bias using a funnel plot, followed by a linear regression test of funnel plot asymmetry (Egger's test) [ 22], was not possible.
Publication bias, which may favor studies with significant findings, was ascertained by inspection of a funnel plot of standard error estimates versus effect size estimates from individual samples and also by a linear regression test [ 14].
