[EMAIL PROTECTED] (Benjamin Kenward) wrote in message
news:<9vnj9m$s2c$[EMAIL PROTECTED]>...
> Hi folks,
>
> Let's say you have a repeatable experiment and each time the result can be
> classed into a number of discrete categories (in this real case, seven).
> If a treatment has no effect, it is known what the expected by chance
> distribution of results between these categories would be. I know that a
> good test to see if a distribution of results from a particular treatment
> is different to the expected by chance distribution is to use a
> chi-squared test. What I want to know is, is it valid to compare just one
> category? In other words, for both the obtained and expected
> distributions, summarise them to two categories, one of which is the
> category you are interested in, and the other containing all the other
> categories. If the chi-square result of the comparison of these categories
> is significant, can you say that your treatment produces significantly
> more results in particularly that category, or can you only think of the
> whole distribution?
Yes, as long as the choice of which category to do it for is not based
on the data... no fair just testing the most extreme one.
Glen
Glen
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