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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

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    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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