RE: st: RE: Re: Kenel density function

[Janet Hill <janethill73@yahoo.co.uk>]

Thank you for your advice. This is not a type of data analysis that I have had to attempt before - it should be an interesting learning curve.

Janet

--- On Wed, 30/6/10, Nick Cox <n.j.cox@durham.ac.uk> wrote:

> From: Nick Cox <n.j.cox@durham.ac.uk>
> Subject: RE: st: RE: Re: Kenel density function
> To: statalist@hsphsun2.harvard.edu
> Date: Wednesday, 30 June, 2010, 10:43
> OK. I'd call this a matter of coarse
> resolution of the data rather than
> binning, which I tend to regard as grouping of original
> measurements
> after data production. If this were my problem I think I
> would look at
> quantile or cumulative distribution functions directly. 
> 
> Nick 
> n.j.cox@durham.ac.uk
> 
> 
> Janet Hill
> 
> Sorry for my ineptitude explaining the data. The master and
> cast are
> scanned and the scanner has a fixed increment of 0.25 mm
> (the smallest
> that can be obtained) so I have binned data at these
> increments and I
> wanted to see how 'reproducible' the scans were.
> Eventually, so I have
> just found out, the experiment will extend to comparing 3
> different
> methods of of making the cast. So my final analysis is
> going to compare
> 3 methods when the outcome is a frequency distribution - if
> that is
> possible.
> 
> Many thanks for your time.
> 
> --- On Tue, 29/6/10, Nick Cox <n.j.cox@durham.ac.uk>
> wrote:
> 
> > You can smooth binned data: the
> > problem, if any, is in over-interpreting
> > results. 
> > 
> > Where does the binning come from? Why aren't unrounded
> data
> > available? 
>  
> > On Behalf Of Janet Hill
>  
> > Thank you for that. There is a single master and 6
> separate
> > impressions
> > have been taken of this so they are uncoupled. The
> > difference between
> > each impression and the master has been measured and
> this
> > gives the
> > binned data.Ideally this should have a value of zero
> for
> > perfect fit. I
> > thought that I could use the kernel density on binned
> data
> > but I
> > obviously need to do some more reading.
> > 
> > Any advice would be gratefully received.
> > 
> > Janet
> > --- On Tue, 29/6/10, Nick Cox <n.j.cox@durham.ac.uk>
> > wrote:
> > 
> > > From: Nick Cox <n.j.cox@durham.ac.uk>
> 
> > > You should tell us more about the
> > > design. Do these come in groups of six, or are
> the
> > six
> > > distributions entirely uncoupled from each other?
> It
> > sounds
> > > as if that information has been omitted from what
> you
> > have;
> > > if so, retrieving it is the first priority. 
> > > 
> > > Either way, trying to reduce all this to
> > Kolmogorov-Smirnov
> > > looks severely problematic to me. As the data
> are
> > already
> > > binned, kernel estimation also looks suspect. 
> > > 
> > > Nick 
> > > n.j.cox@durham.ac.uk
> > > 
> > > 
> > > Janet Hill
> > > 
> > > I would be grateful for some advice. I have some
> data
> > from
> > > an experiment in which the difference between a
> cast
> > and the
> > > master model has been measured. The data consists
> of
> > the
> > > frequency of difference from -8 to + 8 mm in
> steps of
> > 0.25,
> > > and 6 different casts were made. Kernel density
> plots
> > show
> > > obvious differences between the casts but is
> there any
> > way I
> > > can formally test this - or am I missing an
> obvious
> > way to
> > > compare the frequency distributions/ I had
> thought of
> > using
> > > Kolmogorov-Smirnov followed by multiple
> comparisons
> > but I
> > > was not sure how applicable it would be.
> > > 
> > > I am using Stata 11.1
> 
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