I am trying to figure out how to graphically represent different regression models findings (same covariables but run with different strategies).
I ran the same model 6 times with different assumptions and I obtained the different values as well as their upper and lower limit
ex for models 1 (M1 and M2)
Model parameter low_lim value up_lim
M1 SeTUS 0.70 0.82 0.91
M1 SpTUS 0.90 0.94 0.97
M1 pBRD1 0.04 0.09 0.14
M1 pBRD2 0.53 0.73 0.88
M1 pBRD3 0.85 0.94 0.98
M1 pBRD4 0.54 0.71 0.85
M pBRD5 0.30 0.50 0.701
M1 pBRD6 0.14 0.26 0.41
M1 pBRD7 0.06 0.13 0.25
M2 SeTUS 0.68 0.81 0.90
M2 SpTUS 0.90 0.94 0.98
M2 pBRD1 0.04 0.10 0.16
M2 pBRD2 0.50 0.75 0.92
M2 pBRD3 0.91 0.98 1.00
M2 pBRD4 0.65 0.84 0.95
M2 pBRD5 0.28 0.53 0.79
M2 pBRD6 0.09 0.20 0.37
M2 pBRD7 0.02 0.08 0.19
and so on until model 6.
I would like to represent in the same graph a clustered dot plot with the dot representing the value and the upper and lower bound spread grouped by the covariables.
ex: SeTUS for model 1-6 first the SpTUS for model 1-6 and so on until pBRD7 for model 1-6.
I've seen that type of graphs routinely done with R in studies comparing different modelling strategies to see the impact on the regressor findings. I would be more than happy if some of you had any clue.
Thanks so much
Try an SGPLOT procedure.
Use the GROUP= option to colour your models and then you can use a SCATTER statement to plot the markes and error bars.
Here's an example, but you don't need the SERIES statement:
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