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Table 7. 
MTMM matrix output example
 TraitsWeb methodQuestionnaire method
RD1IP1RD2IP2
Web method RD1 a       
IP1 rRD1,IP1 a     
  
Questionnaire method RD2 rRD1,RD2 rIP1,RD2 a   
IP2 rRD1,IP2 rIP1,IP2 rRD2,IP2 a 
  
Convergence validity: Yes if rRD1,RD2 and rIP1,IP2 are high and significant; 
Discriminant validity: Yes if rRD1,RD2 and rIP1,IP2 are bothb > |rRD1,IP2| and |rIP1,RD2|; 
Construct validity without either a combination of trait and method effects or a mono-method bias: Yes if rRD1,RD2 and rIP2,IP2 > |rIP1,RD1| and |rRD2,IP2|. 
 TraitsWeb methodQuestionnaire method
RD1IP1RD2IP2
Web method RD1 a       
IP1 rRD1,IP1 a     
  
Questionnaire method RD2 rRD1,RD2 rIP1,RD2 a   
IP2 rRD1,IP2 rIP1,IP2 rRD2,IP2 a 
  
Convergence validity: Yes if rRD1,RD2 and rIP1,IP2 are high and significant; 
Discriminant validity: Yes if rRD1,RD2 and rIP1,IP2 are bothb > |rRD1,IP2| and |rIP1,RD2|; 
Construct validity without either a combination of trait and method effects or a mono-method bias: Yes if rRD1,RD2 and rIP2,IP2 > |rIP1,RD1| and |rRD2,IP2|. 

Notes (common to Tables 8–13):

a

All traits are measured by single items, no reliability statistic can be calculated.

b

To increase the readability of the results in each table what we mean by “are both” is: rRD1,RD2 > |rRD1,IP2|, rRD1,RD2 > |rIP1,RD2|, rIP2,IP2 > |rRD1,IP2|, and rIP2,IP2 > |rIP1,RD2|

* p < 0.05; ** p < 0.01

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