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Detecting changes in incidence rate

  1. Dec 17, 2011 #1
    I have rare events over time (about 200 incidences) and I'd like to detect when the time rate of these increase, i.e. at which point more events per time start to occur.
    Do you know a solid statistical tool to analyze that? I'd also like to know if the change is real evidence or just random.
  2. jcsd
  3. Dec 17, 2011 #2
    It's somewhat dependent on the temporal profile: isolated random spikes, periodic spikes or waves, or sustained trends. Generally, various applications of moving averages are often used. These are fairly robust and can be adapted to different profiles. You can look up "Moving Average" on the Wiki for a fairly good general discussion. Linear regression models also work well for more sustained trends where you want to test for trends greater or less than 0.

    The following paper shows an application of a combined approach called Autoregressive Integrated Moving Average (ARIMA) for dengue fever.


    EDIT: As an aside, sometimes just inspection is more appropriate than statistical testing if public safety is an issue. You really want to minimize beta error (missing a trend that actually exists). You also will need to control for confounding factors. Differences in reporting and/or detection over time is often the case.
    Last edited: Dec 17, 2011
  4. Dec 19, 2011 #3
    Thanks a lot! I hope I can make use of the information.

    My data is most likely something like a constant rate up to some time and then an increase in frequency. The problem is that it is only about 200 events in total.

    For regression I'm afraid it won't tell me if the trend is with the confidence interval. But I need to read more about it...
  5. Dec 20, 2011 #4
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