Re: st: sampsi and percentages

[Nick Cox <njcoxstata@gmail.com>]

Sure. I was partly in jest, but as a scientist I never feel
constrained by the particular units in which data arrive, especially
if they are not even metric units, let alone natural. Your example
remains units-dependent in that numerator and denominator have quite
different units. Not important unless this is also true of your real
example.

The best way forward for you is likely to be not looking for a canned
approach but simulating datasets of different sizes under plausible
generating processes and seeing what is or is not detectable.

Nick

On Tue, Aug 30, 2011 at 7:33 PM, Ricardo Ovaldia <ovaldia@yahoo.com> wrote:
>
> Thank you Nick. I was specificaly talking about how lenght and weight are recorded in the auto data.
>
>  gen r= length / weight
> . sum r
>     Variable |       Obs        Mean    Std. Dev.       Min        Max
> -------------+--------------------------------------------------------
>            r |        74    .0647308    .0102566   .0475524   .0872222
>
> The ratio is less that one in all observations!
> So the statement was not incorrect.
>
> Regarding your second point: Yes it behaves as a proportion but I cannot use a sample size calculation for proportion to power this study because there is not a true denominator.
> Which brings me back to my original issue of how to power this study.
>
> Ricardo.
>
> Ricardo Ovaldia, MS
> Statistician
> Oklahoma City, OK
>
>
> ----- Original Message -----
> From: Nick Cox <njcoxstata@gmail.com>
> To: statalist@hsphsun2.harvard.edu
> Cc:
> Sent: Tuesday, August 30, 2011 10:02 AM
> Subject: Re: st: sampsi and percentages
>
> Two points:
>
> 1. In terms of your example, length/weight is not always < 1. The
> value of that ratio is crucially dependent on some choice of units of
> measurement. Suppose I measure my (wife's) car's length in centimetres
> and its weight (mass) in tonnes, for example.
> You can call this pedantry but I react to incorrect statements!
>
> 2. More importantly, if something is bounded by (0,1) -- can we take
> that pair of () literally as implying 0 < data < 1? -- then it will
> behave like a proportion regardless of how the calculation was done.
> For example, an average very near 0 can only be achieved if all values
> are near 0 and so the variance will be very small, and similarly for
> an average near 1. However, that may not help much.
>
> Nick
>
> On Tue, Aug 30, 2011 at 3:45 PM, Ricardo Ovaldia <ovaldia@yahoo.com> wrote:
>>
>> Thank you, but these are not proportions. They are intensity measures. You can think of them as ratios of two continous things.
>> For example with the auto data, they could be the ratio of car's length  to weight (length / weight) which is always between 0 and 1.
>> Now less say that you want to compare these ratio between between foreign and domestic cars.
>>
>> Ricardo
>>
>> Ricardo Ovaldia, MS
>> Statistician
>> Oklahoma City, OK
>>
>>
>> ----- Original Message -----
>> From: "Ariel Linden, DrPH" <ariel.linden@gmail.com>
>> To: statalist@hsphsun2.harvard.edu
>> Cc:
>> Sent: Tuesday, August 30, 2011 7:51 AM
>> Subject: re: st: sampsi and percentages
>>
>> Ricardo,
>>
>> I may be mistaken here, but it seems you have two proportions (if it's
>> bounded between 0,1 then you have a numerator and a denominator for each
>> group).
>>
>> If that is truly the case, you can use sampsi for proportions:
>>
>> . sampsi 0.25 0.4
>>
>> Estimated sample size for two-sample comparison of proportions
>>
>> Test Ho: p1 = p2, where p1 is the proportion in population 1
>>                     and p2 is the proportion in population 2
>> Assumptions:
>>
>>         alpha =  0.0500  (two-sided)
>>         power =  0.9000
>>             p1 =  0.2500
>>             p2 =  0.4000
>>         n2/n1 =  1.00
>>
>> Estimated required sample sizes:
>>
>>             n1 =      216
>>             n2 =      216
>>
>> I hope this helps
>>
>> Ariel
>>
>> Date: Mon, 29 Aug 2011 11:40:33 -0700 (PDT)
>> From: Ricardo Ovaldia <ovaldia@yahoo.com>
>> Subject: st: sampsi and percentages
>>
>>
>>
>> I need to compute sample size and power for a study comparing two group on a
>> measurement bounded by (0,1), (a measure of intensity).
>> I was thinking about using -sampsi- to power on the difference of means.
>> However, this seems strange to me, is there another way to power such
>> comparison?
>>

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