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How can I extrapolate a natural history using multiple data changes over time.

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    Unhappy How can I extrapolate a natural history using multiple data changes over time.

    I have a problem that I have difficulty explaining but here goes. I have multiple data sets that I want to use to see what happens over time.

    For example, i know that in 1 case, over 500 days, a the test went up from 250-500 over 4 months. I have another case where the test went up from 1-40 over 6 months and another case where the value went from 60-200 over 5 months and 200-1000 over 8 months.

    How do I plot this and put it altogether to say what happens with the test over time?

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    Re: How can I extrapolate a natural history using multiple data changes over time.

    Hi,

    It would assist greatly of you could upload the data so that we can see the layout.

    In general though I think I'd summarise the data to record the Minimum and Maximum values for periods of 1,2,3....n months and then create a column chart with the number of months on the x axis and the columns showing the min/max spread on the y axis.

    As to how you summarise the data we can only really say when we see the layout.
    Richard Buttrey

    If any of the responses have helped then please consider rating them by clicking the small star icon below the post.

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    Re: How can I extrapolate a natural history using multiple data changes over time.

    I see. The problem is the data is health protected so I can give you an example table I suppose.

    ID Sample 1 Sample 1 date Sample 2 Sample 2 date delta sample delta dates
    A 100 1/1/2016 200 1/15/2016 100 14
    B 2000 1/1/2012 5000 6/1/2013 3000 517
    C 1234 2/4/2014 4566 3/18/2014 3332 42
    D 256 5/28/1983 250 6/28/1983 -6 31

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    Re: How can I extrapolate a natural history using multiple data changes over time.

    Sorry here is a better formatted version.
    ID Sample 1 Date 1 Sample 2 Date 2 Delta sample Delta time
    A 100 1/1/2016 200 1/15/2016 100 14
    B 2000 1/1/2012 5000 6/1/2013 3000 517
    C 1234 2/4/2014 4566 3/18/2014 3332 42
    D 256 5/28/1983 250 6/28/1983 -6 31

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