Hi Statalisters,
This might be basic, but I'm new to stats.
I am investigating the impact of X variable on total Y variableand its three dimensions (i.e. Y1, Y2, and Y3), where total Y = Y1+Y2+Y3, using four models:
Y= α + β_1X + control variables
Y1= α + β_1X + control variables
Y2= α + β_1X + control variables
Y3= α + β_1X + control variables
Assuming that X has a positive impact on total Y and its three dimensions, one of my research hypotheses is that the impact of X variable in models that examine Y1, Y2, Y3 are expected to differ significantly from the model that investigates total Y.
In this regard, please how can I test this hypothesis? How can I know if the impact of X variable on each dimension significantly differ from total Y, and across the separate three dimensions? Please note that I am using cross-sectional data if this information is relevant.
Your help and valuable time are much appreciated!!
Thank you very much in advance.
This might be basic, but I'm new to stats.
I am investigating the impact of X variable on total Y variableand its three dimensions (i.e. Y1, Y2, and Y3), where total Y = Y1+Y2+Y3, using four models:
Y= α + β_1X + control variables
Y1= α + β_1X + control variables
Y2= α + β_1X + control variables
Y3= α + β_1X + control variables
Assuming that X has a positive impact on total Y and its three dimensions, one of my research hypotheses is that the impact of X variable in models that examine Y1, Y2, Y3 are expected to differ significantly from the model that investigates total Y.
In this regard, please how can I test this hypothesis? How can I know if the impact of X variable on each dimension significantly differ from total Y, and across the separate three dimensions? Please note that I am using cross-sectional data if this information is relevant.
Your help and valuable time are much appreciated!!
Thank you very much in advance.
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