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Re: st: ANOVA repeated measures


From   Rune Nielsen <nielsenrune@me.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: ANOVA repeated measures
Date   Tue, 06 Nov 2012 20:56:23 +0100

Thanks a lot to everyone!

Best wishes from Rune

6. nov. 2012 kl. 16:16 skrev "Lythgoe, Dan" <D.Lythgoe@liverpool.ac.uk>:

> Rune, 
> 
> ‘ANCOVA’ code would be as follows when reshaped wide:
> 
> reg postbal prebal i.flush
> 
> This is comparing the postbal between flush groups, correcting for the prebal. You might then want to do some residual diagnostics:
> 
> predict yhat
> predict stu, rstudent
> qnorm stu
> scatter stu yhat
> 
> I don't think that the -bysort- command you are using is doing what you intend; I think this would run two separate paired t-tests whereas you want an unpaired comparison of the two groups.
> 
> Many thanks
> Dan Lythgoe
> 
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Rune Nielsen
> Sent: 06 November 2012 14:29
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: ANOVA repeated measures
> 
> Thank you for your kind answer. 
> The linear mixed model is probably to difficult for me at the moment since I'm just trying to summarize some preliminary analyses and don't have the opportunity right now to do extensive reading. 
> 
> I've tried analyzing on the difference scores, but got the impression of somehow loosing power. When I reshaped the dataset (to wide), stratified by flush and did t-tests on the difference I found significant results (bysort flush: ttest bal1=bal2). But when I did as you recommended they where not even close to significant (ttest baldiff by(flush)). 
> 
> Would you be able to provide an example of an ancova syntax? 
> 
> Again, thank you!
> 
> Best wishes from Rune
> 
> ---
> Rune Nielsen, MD, PhD, postdoctoral fellow
> Institute of Medicine
> Department of Thoracic Medicine
> Haukeland University Hospital
> N-5021 Bergen
> Norway
> 6. nov. 2012 kl. 15:04 skrev "JVerkuilen (Gmail)" <jvverkuilen@gmail.com>:
> 
> 
> Hmmm, well you have a few choices as to how to analyze these data. One
> is simply to convert to difference scores (post - pre) and do a
> two-sample t-test comparing the flush and non-flush group. This uses
> the subjects as their own controls.
> 
> There is an equivalent linear mixed model (depending on how you
> estimate the model it will be exactly equivalent, or just close). Wit
> the data laid out long, use -xtmixed- you'd use a subject indicator
> and flush as a fixed effects predictor.
> 
> You could also decide to use an ANCOVA approach. Reshape wide and use
> the pre as a regressor along with the intervention.
> 
> It's not 100% clear which is the right thing to do. A lot depends on
> how correlated pre and post are likely to be for the controls.
> 
> 
> 
> On Tue, Nov 6, 2012 at 8:55 AM, Rune Nielsen <nielsenrune@me.com> wrote:
> 
> Dear statalist members,
> 
> We have done a simple pilot study where we measure the number of bacteria on
> the tip of a bronchoscope two times on the same 20 subjects. Half of these
> subjects have received an intervention to reduce the number of bacteria. So
> in a long dataset with 40 observations  I have the following variables
> Idnr - subject ID
> meas - binary variable indicating first (=1) or second (=2) measurement
> flush - binary variable whether the subject have received (=1) or not (=0)
> the intervention
> bal - measurement of bacterial load
> 
> What I would like to do, is to test whether the difference between
> measurement 1 and measurement 2 is  depending on whether they have received
> the intervention. I've tried various ANOVA syntaxes, but my limited
> knowledge won't quite get me there.
> 
> Probably this reveals my incompetence, but nevertheless I hope for an answer
> that is understandable for a non-statisician.
> 
> Best wishes,
> 
> Rune Nielsen
> 
> ---
> Rune Nielsen, MD, PhD, postdoctoral fellow
> Institute of Medicine
> Department of Thoracic Medicine
> Haukeland University Hospital
> N-5021 Bergen
> Norway
> 
> 
> 
> -- 
> JVVerkuilen, PhD
> jvverkuilen@gmail.com
> 
> "Thus the typical citizen drops down to a lower level of mental
> performance as soon as he enters the political field. He argues and
> analyzes in a way which he would readily recognize as infantile within
> the sphere of his real interests. He becomes a primitive again. His
> thinking becomes associative and affective."  ---Joseph A. Schumpeter,
> Capitalism, Socialism and Democracy, 1950, p. 262.
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