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  • Data quality control check with CUMSUM

    Hi all,

    I have a big data set and am trying to QC some variables such as blood pressure and cholesterol measurement. I am trying to see if there is any drift pattern/consistency of the measurements taken by the devices we have overtime. Basically we have multiple daily (1 year worth of data) measurements for each variable and devices. Eg:

    device date sbp dbp cholesterol
    1 22/8/18 108
    1. 22/8/18 110
    2 22/8/18 115
    2 23/8/18 118
    2 23/8/18 115

    My questions:
    1. What is the best way to analyse these dataset? Do you think CUMSUM plot is applicable? Any examples?
    2. I tried taking the weekly average reading and then do a basic scatter plot ? But I have problem adding the mean line, and +/- SD line into the plot to identify outlier measurements. I keep getting error message when using the common yline? Eg of my command:

    global mean1= r(mean)
    global lowerCL1= r(mean) - 1*r(sd)
    global upperCL1= r(mean) + 1*r(sd)


    twoway (scatter ave_height weekly_date, ///
    legend(off) mcolor(black) ///
    yline($mean1, lpattern(shortdash) lcolor(gray))///
    yline($lowerCL1, lpattern(dash) lcolor(gray)) ///
    yline($upperCL1, lpattern(dash) lcolor(gray)) ///
    graphregion(color(white)) ylabel(, grid glcolor(gs14)) ///
    ylabel(150(1)154) xlabel(1(2)60) ///
    aspectratio(1.09) //



    Please help!

    Many thanks!
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