Multiple comparison adjustment using the Bonferroni procedure was made for the 13 domain measures and two summary scales of the CHQ-PF28, all five child productivity measures assessed and all four measures of the WPAI due to number of hypotheses tested simultaneously for these measures.
After adjustment using multiple logistic regression, only a 5-min Apgar score ≤3 and babies with at least one major morbidity had significantly independent effects on neonatal survival.
Applying multiple testing adjustments using permutations analysis we identified a significant association in ABAT, but not in any of the other genes, showing that ABAT is a GERD associated gene in our pediatric GERD population.
The exposure and the potential confounders will be modelled in relation with the outcome variable for adjustment using a multiple-predicative regression model.
ANCOVAs with multiple adjustments were used to disclose possible group differences in HRV.
Of the 36 trials reporting more than 10% missing data, 16 (44%) performed a sensitivity analysis: 4 used complete case, 2 used simple imputation, 1 used simple and multiple imputation, 6 used multiple imputation, 2 made adjustments using auxiliary data, and 1 approach was unclear.
Step 6 (Adjustment for multiple testing) P-value adjustments using Bonferroni, Sidak (A technique slightly less conservative than Bonferroni) and False Discovery Rate (FDR) are corrected for total tests performed and are calculated using simple functions of the raw p-values.
We then used a multiple adjustment model adjusted for age, sex, BMI, MMSE, number of prescribed medications, hypertension, heart disease, diabetes mellitus, osteoporosis and GDS (model 2).
This is without applying Bonferroni's adjustment for multiple comparisons; using this adjustment, a p-value of approximately < 0.0007 would be required for a single comparison to be statistically significant.
Lognormality of the distribution of the reporting ratio was assessed based on a Kolmogorov-Smirnov test (α = 0.05).. Confidence intervals for PLM nausea rates were calculated using the Clopper-Pearson exact method, and adjusted for multiple comparisons using Bonferroni adjustment.
