Hi, thank you! Is it equivalent of doing a partial correlation plot? I'm having some trouble finding an easy way to plot this partial correlation: pcor.test(data$X1,data$X2, data$Z method = "spearman") .... Z is the controlled variable, which influences both X1 and X2 (I'm using R studio) Ps: why are all variables centered?
These are similar, but different. I would use car::avPlots() if you need scatterplots. Would a bar plot of the estimates from ppcor::pcor() work? Centering and scaling the data helps make it easier to evaluate the magnitude of the values.
Okay how about this analogy. If I have an all-star goalie, would it improve my team to get another all-star goalie? Predictor variables with flat added-variable plots have little to add to the model. Adding such a variable to a model does not improve the model. Much like double filling a position does not improve a team.
This was a really clear explanation and good example. I understand it now. Thank you!
Better than any textbook explanation I've seen, thank you so much!
Thank you so much for this video! It has solved my very important doubts that I couldn't find anywhere else.
Most helpful explanation. Thank you very much!
Thank you for the video!!! Currently studying stats at ucla. This helps me round out the math with a conceptual, intuitive understanding
What if you get a steep negative slope line in your added variable plot?
@@nasheedjafri3564 If a variable has a steep slope positive or negative then you want to include it in your model.
so helpful thanks so much
Hi, thank you! Is it equivalent of doing a partial correlation plot? I'm having some trouble finding an easy way to plot this partial correlation: pcor.test(data$X1,data$X2,
data$Z method = "spearman") .... Z is the controlled variable, which influences both X1 and X2 (I'm using R studio) Ps: why are all variables centered?
These are similar, but different. I would use car::avPlots() if you need scatterplots. Would a bar plot of the estimates from ppcor::pcor() work? Centering and scaling the data helps make it easier to evaluate the magnitude of the values.
This was great! Where can we get the doc or written instructions?
I put the files in the shared files section of my website. www.statistics.ninja
thanks
Are you using R or Stata?
@@statisticsninja thank you for responding.
I understood it well until you use American football as an example.
Okay how about this analogy. If I have an all-star goalie, would it improve my team to get another all-star goalie? Predictor variables with flat added-variable plots have little to add to the model. Adding such a variable to a model does not improve the model. Much like double filling a position does not improve a team.