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Re: st: Statistical significance of standardized rates


From   Nick Cox <njcoxstata@gmail.com>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Statistical significance of standardized rates
Date   Thu, 4 Apr 2013 17:14:11 +0100

Sorry, but I can't add to what I said. You may need to say more about
the data and you do need an expert who knows these methods backwards.
Nick
njcoxstata@gmail.com


On 4 April 2013 17:03, Karman Tandon <karmantandon@gmail.com> wrote:
> Hi Nick,
> I also noticed that the confidence intervals have zero length. Here is
> a summary of the dstdize I ran:
>
> dstdize x pop a b c d, by(quartiles)
>
> - x is mortality, a dichotomous 1/0
> - pop is the entire population in my data set
> - a, b, c, d are a mix of continuous and dichotomous variables
> - quartiles is the quartile group that each member of the population
> falls into based on a continuous variable "e" that is not included in
> the a,b,c,d being standardized by.
>
> Is this an appropriate use of the command?
>
> Thank you,
> Karman
>
> On Thu, Apr 4, 2013 at 11:57 AM, Nick Cox <njcoxstata@gmail.com> wrote:
>> -dstdize- is a command, not a function.
>>
>> Before you proceed further, note that the confidence intervals appear
>> to be of essentially zero length. That seems implausible, but if it's
>> true, any difference you like is significant at conventional levels.
>> Getting a P-value is moot. However, I'd be suspicious without being
>> sure that the instructions were correct.
>>
>> Nick
>> njcoxstata@gmail.com
>>
>> On 4 April 2013 16:44, Karman Tandon <karmantandon@gmail.com> wrote:
>>> Hi,
>>>
>>> I've used the dstdize function to standardize/adjust across a number
>>> of variables. My data looks like this:
>>>
>>> Summary of Study Populations:
>>>      quartile        N      Crude     Adj_Rate       Confidence Interval
>>>  --------------------------------------------------------------------------
>>>         1           290   0.196552     0.060000    [  0.060000,    0.060000]
>>>         2           233   0.124464     0.030526    [  0.030526,    0.030526]
>>>         3           216   0.087963     0.020000    [  0.020000,    0.020000]
>>>         4           210   0.066667     0.014737    [  0.014737,    0.014737]
>>>
>>> How do I determine p-values for the significance of the adjusted rates
>>> compared to one another?
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