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Table 8 Pairwise differences of the ten treatment means

From: Network-meta analysis made easy: detection of inconsistency using factorial analysis-of-variance models

 

benf

metf

migl

piog

plac

rosi

sita

SUal

vild

acar

-0.1045 (0.3659)

0.2870 (0.2504)

0.1085 (0.3280)

0.2880 (0.3054)

-0.8414 (0.2384)

0.3924 (0.2526)

-0.2714 (0.4165)

-0.4238 (0.2568)

-0.1414 (0.4159)

benf

 

0.3915 (0.3153)

0.2130 (0.3575)

0.3925 (0.3492)

-0.7369 (0.2776)

0.4968 (0.3038)

-0.1669 (0.4401)

-0.3194 (0.3622)

-0.0369 (0.4395)

metf

  

-0.1785 (0.2703)

0.0010 (0.2176)

-1.1284 (0.1494)

0.1053 (0.1600)

-0.5584 (0.3727)

-0.7109 (0.2272)

-0.4284 (0.3721)

migl

   

0.1795 (0.3093)

-0.9499 (0.2253)

0.2839 (0.2569)

-0.3799 (0.4091)

-0.5324 (0.3238)

-0.2499 (0.4085)

piog

    

-1.1294 (0.2119)

0.1043 (0.2163)

-0.5594 (0.4019)

-0.7119 (0.2914)

-0.4294 (0.4013)

plac

     

1.2337 (0.1235)

0.5700 (0.3414)

0.4175 (0.2326)

0.7000 (0.3408)

rosi

      

-0.6637 (0.3631)

-0.8162 (0.2290)

-0.5337 (0.3624)

sita

       

-0.1525 (0.4132)

0.1300 (0.4824)

SUal

        

0.2825 (0.4126)

  1. Means for the diabetes example of Senn et al. [7] computed from model (2), dropping the design × treatment interaction (G.T) and modelling heterogeneity (G.S.T) as random. Table reports pairwise mean differences (and associated standard errors).