Mediation testing
Posted: Sat Mar 07, 2020 6:40 pm
Hello. I am a beginner in SmartPLS and now using smartpls 3.2.9. I have been reading Zhao 2010, Hair 2017, Memon 2018, and several more papers. But since I'm new to both statistics and pls sem, I get easily confused. In my model, I have 3 IVs going through each of 4 MVs into 1 DV as below:
IV1 --> MV1 --> DV
IV1 --> MV2 --> DV
IV1 --> MV3 --> DV
IV1 --> MV4 --> DV
IV2 --> MV1 --> DV
IV2 --> MV2 --> DV
IV2 --> MV3 --> DV
IV2 --> MV4 --> DV
IV3 --> MV1 --> DV
IV3 --> MV2 --> DV
IV3 --> MV3 --> DV
IV3 --> MV4 --> DV
My questions regarding the test are:
1) When i draw the path model in smartpls3, should i connect
IV1 --> DV,
IV2 -- > DV,
IV3 --> DV too?
2) What is the difference between total indirect effect and specific indirect effect? If specific indirect effect are mostly not significant (pvalue), but total indirect effect is significant, does it means there is mediation or not?
3) I read about decision tree in Zhao 2010. I understand that a&b are indirect effects while c is direct effect. ( a = IV -> MV, b= MV -> DV, and c = IV -> DV). However, which value is actually a, b and c? Are the values are the original sample?
4) How to get direct effect? I understand total effect = total indirect + direct effect. Which value should i minus to get direct effect?
I hope i can get answers. I've been watching youtube videos too but I don't quite understand. Thank you..
IV1 --> MV1 --> DV
IV1 --> MV2 --> DV
IV1 --> MV3 --> DV
IV1 --> MV4 --> DV
IV2 --> MV1 --> DV
IV2 --> MV2 --> DV
IV2 --> MV3 --> DV
IV2 --> MV4 --> DV
IV3 --> MV1 --> DV
IV3 --> MV2 --> DV
IV3 --> MV3 --> DV
IV3 --> MV4 --> DV
My questions regarding the test are:
1) When i draw the path model in smartpls3, should i connect
IV1 --> DV,
IV2 -- > DV,
IV3 --> DV too?
2) What is the difference between total indirect effect and specific indirect effect? If specific indirect effect are mostly not significant (pvalue), but total indirect effect is significant, does it means there is mediation or not?
3) I read about decision tree in Zhao 2010. I understand that a&b are indirect effects while c is direct effect. ( a = IV -> MV, b= MV -> DV, and c = IV -> DV). However, which value is actually a, b and c? Are the values are the original sample?
4) How to get direct effect? I understand total effect = total indirect + direct effect. Which value should i minus to get direct effect?
I hope i can get answers. I've been watching youtube videos too but I don't quite understand. Thank you..