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Re: st: Statistical significance of standardized rates
From
Nick Cox <[email protected]>
To
"[email protected]" <[email protected]>
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
[email protected]
On 4 April 2013 17:03, Karman Tandon <[email protected]> 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 <[email protected]> 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
>> [email protected]
>>
>> On 4 April 2013 16:44, Karman Tandon <[email protected]> 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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