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Re: st: Calculating pooled estimates using random-effects logistic regression


From   Philipp Do <[email protected]>
To   [email protected]
Subject   Re: st: Calculating pooled estimates using random-effects logistic regression
Date   Mon, 17 Feb 2014 16:30:32 +0100

Hi,

Thanks for your informative response!

For claification: As part of meta-analysis I want to calculate a
pooled estimates of the survival rates from different studies -
similar to the paper by Cabibbo et al. - see
http://onlinelibrary.wiley.com/doi/10.1002/hep.23485/pdf

Best,

Philipp Do

2014-02-17 16:11 GMT+01:00 Alfonso Sánchez-Peñalver
<[email protected]>:
> Hi,
>
> I don't understand what you mean by pooled estimates, since from the data you show each observation is a different study, and no study is repeated in more than one observation. I also don't understand what kind of model you want to estimate here with a logistic regression, since you don't have an explanatory variable, as the number of patients ought to be what you refer to as sample size and thus used as weights.
>
> Having said that, if you were to have more variables that you could use to estimate a logistic regression model, and since your response variable (survival rate) is a fractional response variable, you could consistently estimate the logistic model using the -glm- command with the -familyname- option set to binomial, and the -linkname- option set to logit, since -glm- accepts weights. For examples type -help glm-. The seminal paper on simple (not pooled) fractional response variables is:
>
> Papke, Leslie E. and Jeffrey M. Wooldridge (1996), "Econometric Methods For Fractional Response Variables With An Application to 401(K) Plan Participation Rates," Journal of Applied Econometrics, Vol. 11, 619-632.
>
> When you indeed have a pooled (where certain units of interest are observed more than once) dataset with a fractional response variable, the paper to read is
>
> Papke, Leslie E. and Jeffrey M. Wooldridge (2008), "Panel data methods for fractional response variables with an application to test pass rates," Journal of Econometrics, Vol. 145, 121-133
>
> Best,
>
> Alfonso Sanchez-Penalver, PhD.
>
> Visiting Assistant Professor
> Suffolk University
>
> Senior Instructor
> University of Massachusetts, Boston
>
>
> On Feb 17, 2014, at 9:21 AM, Philipp Do <[email protected]> wrote:
>
>> I want to calculate pooled estimates of 1-year survival rates from
>> several studies using random-effects logistic regression analysis
>> (sample weighting should be applied according to the sample size).
>> What is the most appropriate way to perform this analysis with Stata?
>> Can you give me an example on the appropriate command using the data
>> below?
>>
>> Study   No. of patients     1-year survival rate (%)
>> #1                46                  40
>> #2                21                  31
>> #3                36                  47
>> #4                25                  33
>> #5                11                  27
>> #6                16                  39
>> #7                46                  37
>> #8                29                  22
>> #9                62                  30
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