Hi all,
I am currently running a quantile regression model using the command qreg2 to report median difference with 95% CI.
My outcome is continuous and predictor is binary (treatment 1 or treatment 2). The reason I am using quantile regression is because the outcome data is skewed and when running the Shapiro-Wilk test for normality after normal regression p was reported as <0.05.
My code adjusts for minimisation factors (age, multiple and centre) and a cluster to allow for the correlation between multiple births. I wanted to know if the way I've built this model logically and statistically makes sense, and/or if there is any other command that is a better fit for my data.
Code in Stata:
qreg2 outcome i.treatment i.multiple age i.centreID, cluster (MultipleClusterID) quantile(0.5)
Any advice is appreciated
I am currently running a quantile regression model using the command qreg2 to report median difference with 95% CI.
My outcome is continuous and predictor is binary (treatment 1 or treatment 2). The reason I am using quantile regression is because the outcome data is skewed and when running the Shapiro-Wilk test for normality after normal regression p was reported as <0.05.
My code adjusts for minimisation factors (age, multiple and centre) and a cluster to allow for the correlation between multiple births. I wanted to know if the way I've built this model logically and statistically makes sense, and/or if there is any other command that is a better fit for my data.
Code in Stata:
qreg2 outcome i.treatment i.multiple age i.centreID, cluster (MultipleClusterID) quantile(0.5)
Any advice is appreciated
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