[R-sig-ME] geometric mean regression

[Kevin E. Thorpe]

Back transformation can be tricky. You should also look at smearing 
estimators. The package Hmisc has a function called smearingEst() that 
you might like to check.

Kevin

On 03/31/2018 06:37 PM, Ahmad wrote:
> Hi Kevin
> 
> Thanks for your email,
> Yes, I almost figured out how get this done. I needed to get the exp() of intercept for the reference group and exp() of coefficient*exp(intercept) for the other group.
> 
> When I was trying this for geometric of 95%CI, the results don't seem quite right. I found an article that if I get the exp() of lsmeans (emmeans) these will produce the correct geometric outputs. Not sure why when I do these manually using the exp() of intercept and coefficient of lm- the outputs are not identical, but close enough.
> 
> Ahmad
>       
> 
> -----Original Message-----
> From: Kevin E. Thorpe <kevin.thorpe at utoronto.ca>
> Sent: Sunday, 1 April 2018 12:22 AM
> To: Ahmad <ahmadr215 at tpg.com.au>
> Subject: Re: [R-sig-ME] geometric mean regression
> 
> Maybe I'm missing something, but doesn't linear regression on log(y) accomplish this?
> 
> Kevin
> 
> On 03/29/2018 08:25 AM, Ahmad wrote:
>> Hi All
>>
>>    
>>
>> I have a dataset and I have been asked to generate geometric means
>> from the linear regression for different groups (2 groups).
>>
>> In fact my data is repeated measures, and I intend to use a
>> mixed-effects regression model with repeated measures. But I thought I
>> can learn how to do this for a simple geometric mean regression, I
>> should be able to translate this into a mixed model.
>>
>>    
>>
>> Any help would be greatly appreciated!
>>
>>    
>>
>> Thanks
>>
>>    
>>
>> Ahmad
>>
>>    


-- 
Kevin E. Thorpe
Head of Biostatistics,  Applied Health Research Centre (AHRC)
Li Ka Shing Knowledge Institute of St. Michael's Hospital
Assistant Professor, Dalla Lana School of Public Health
University of Toronto
email: kevin.thorpe at utoronto.ca  Tel: 416.864.5776  Fax: 416.864.3016