Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Ricardo Ovaldia <ovaldia@yahoo.com> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: sampsi and percentages |

Date |
Tue, 30 Aug 2011 11:39:24 -0700 (PDT) |

Thank you Ronan. My original question was whether it makes sense to compute power and sample size using means in a study similar to the example I gave with the auto data. You are correct that ratio can be greater than 1, while a proportion cannot. However in my case the ratio will always be between 0 and 1. I am wondering wheter powering on the difference of means in such comparisons makes sense. Ricardo Ricardo Ovaldia, MS Statistician Oklahoma City, OK ----- Original Message ----- From: Ronan Conroy <rconroy@rcsi.ie> To: "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> Cc: Sent: Tuesday, August 30, 2011 10:10 AM Subject: Re: st: sampsi and percentages On 2011 Lún 30, at 15:45, Ricardo Ovaldia 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. > I am a little confused. A ratio can be greater than 1, while a proportion cannot. In your example, however, you are asking if the difference in weight between foreign and domestic cars is explained by the difference in length between them. . regress weight length foreign Source | SS df MS Number of obs = 74 -------------+------------------------------ F( 2, 71) = 316.54 Model | 39647744.7 2 19823872.3 Prob > F = 0.0000 Residual | 4446433.7 71 62625.8268 R-squared = 0.8992 -------------+------------------------------ Adj R-squared = 0.8963 Total | 44094178.4 73 604029.841 Root MSE = 250.25 ------------------------------------------------------------------------------ weight | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- length | 31.44455 1.601234 19.64 0.000 28.25178 34.63732 foreign | -133.6775 77.47615 -1.73 0.089 -288.1605 20.80555 _cons | -2850.25 315.9691 -9.02 0.000 -3480.274 -2220.225 ------------------------------------------------------------------------------ Length is a significant determinant of weight, and adjusted for this there is no significant difference between domestic and foreign cars (the effect size is interesting, but the standard error is very large). Is this analogous to what you had in mind? Ronán Conroy rconroy@rcsi.ie Associate Professor Division of Population Health Sciences Royal College of Surgeons in Ireland Beaux Lane House Dublin 2 * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**re: st: sampsi and percentages***From:*"Ariel Linden, DrPH" <ariel.linden@gmail.com>

**Re: st: sampsi and percentages***From:*Ricardo Ovaldia <ovaldia@yahoo.com>

**Re: st: sampsi and percentages***From:*Ronan Conroy <rconroy@rcsi.ie>

- Prev by Date:
**st: Fit chi2 as in gammafit** - Next by Date:
**Re: st: sampsi and percentages** - Previous by thread:
**Re: st: sampsi and percentages** - Next by thread:
**re: Re: st: sampsi and percentages** - Index(es):