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This post-hoc procedure adjusts for all pairwise comparisons and simultaneous inference.
The LMS curve fitting procedure adjusts for skewness so that the percentile values and z-scores generated by the LMS values are robust when the data are not normally distributed.
Our procedure adjusts for problems with multiplicity and also forces investigators and consumers of clinical research to judge clinical significance.
The MLR procedure adjusts for possible confounding effects between independent variables and helps identify those which are the best predictors for each of the poor HRQOL indicators.
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All analyses were performed using the statistical program SAS 9.2 'surveylogit' procedure, adjusted for sample clustering at the level of primary sampling units.
The between schedule comparison and the RTS,S/AS01E versus rabies comparison were done using the mixed model procedure adjusted for multiple comparisons using the Bonferroni method to correct for type I error.
All analyses were performed separately for women and men, as well as for the total group, and multivariate logistic regression analysis using a stepwise procedure, adjusting for significant interactions (considering a threshold level of 0.15), was used to assess the relationship between independent variables (mtDNA, APOE4 status, age and gender) and the outcome.
Pairwise differences were identified using the Bonferroni post hoc analysis procedure adjusted for multiple comparisons.
An FDR, using the BH procedure, adjusting for multiple tests was also calculated.
The primary endpoint was analyzed by using the Cochran-Mantel-Haenszel (CMH) procedure adjusted for center.
Associations of quantitative variables with menopausal status were examined by analysis of covariance (General Linear Model procedure) adjusting for age.
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