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Most adjustment methods have focused on adjustments of the P-value threshold, but adjusted confidence intervals can often be calculated based on an adjusted P-value and an effect estimate [ 12, 35, 36].
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Several studies have been conducted to compare the performance of the two most common risk adjustment methods, the Charlson and the Elixhauser methods [ 9, 15, 18, 19].
Here, we did not apply the FDR control at the step of finding signature hubs because the statistical powers of most multiple test adjustment methods are decreased in the presence of wide and correlated expression changes of genes in cancers [ 30, 31].
For comparison we also consider the Trim & Fill method [ 11], which is probably the most widely used adjustment method presently.
Risk adjustment methods are commonly used to address this threat with the most frequently used methods being the Charlson [ 1] and the Elixhauser [ 2] methods.
The statistical properties of baseline adjustment methods are complex and often poorly understood, resulting in confusion about the choice of the most appropriate statistical strategy.
Brown CC, Kipnis V, Freedman LS, Hartman AM, Schatzkin A, Wacholder S. Energy adjustment methods for nutritional epidemiology: the effect of categorization.
Anyway, the above two adjustment methods are both feasible.
For different TI adjustment methods, our schemes have different names.
However, that decline reflected the government's seasonal adjustment methods.
The following comorbidity adjustment methods were used.
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