Date: Wed, 24 Aug 2005 14:51:42 -0600
Reply-To: Nate Wojcik <nate.wojcik@gmail.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Nate Wojcik <nate.wojcik@gmail.com>
Subject: Re: Nonparametric vs. Parametric
In-Reply-To: <20050824212446.r9d58qhix868go0g@webmail.statisticsdoc.com>
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keith,
first of all, the design is looking at the changes to soil
properties caused by fires within different ecosystems. there are a
series of DVs that are continuous variables measuring different soil
properties, i.e. phosphorus, nitrogen, carbon, pH. categorical IVs
would include soil type, vegetation type, fire treatment, and chemical
and seed amendments. i am not exactly clear on what you mean by a
non-arbitrary zero point, but i can say that none of the variables
measure negative values. the DV is not measured directly on the same
exact soil sample because the soil has to be extracted for chemical
analysis. but the post burn sample is extracted before analysis
adjacent to where the pre sample was collected from, with similar
texture and vegetation cover. raw data is organized to where the pre
and post samples are linked (by plot # and location) and the intervals
between pre- and post-burn treatments were the same across subjects.
nate
On 8/24/05, starborn@statisticsdoc.com <starborn@statisticsdoc.com> wrote:
> Keith Starborn
> www.statisticsdoc.com
>
> Nate -
>
> You ask a series of very interesting questions. Just to start with one - the
> log transformation of the dependendent variable - what is the nature of
> the DV?
> Does it have a non-arbitrary zero point? If so, it would be appropriate to
> treat the DV as a ratio measure and a log transformation of the DV might well
> be very informative.
>
> You also mention that you are working with pre and post burn treatments. Does
> this mean that the DV is measured on the same subjects at two time-points? Do
> you have the raw data organized so you can link measures on the same subjects
> at two time points? Are the intervals between pre- and post measures similar
> across subjects? If you can meet these conditions, a repeated measures ANOVA
> would be informative.
>
> Best,
>
> KS
>
> Quoting Nate Wojcik <nate.wojcik@gmail.com>:
>
> > i am currently analyzing data and i have come across a few ideas
> > that i need clarification on. my design consists of a single DV and
> > multiple IV's (with one IV containing greater than two levels). my
> > hypotheses have been structured such that a multi-way ANOVA
> > (three-way) should be sufficient. however, i am unable to satisfy the
> > assumption of a normally distributed population. first of all, when
> > determining the distribution and variances for a multi-way ANOVA,
> > should the sample distribution be analyzed by grouping factors?
> > second, since there are not any nonparametric equivalents for designs
> > with more than two IV's (to the best of my knowledge, unless a SRH
> > extension works, but how?), how important is it to meet all of the
> > assumptions of a three-way ANOVA. furthermore, if i can transform my
> > data (log and log+constant) to allow both the skewness and the
> > kurtosis to approach zero, will this suffice a normally distributed
> > population. are there any helpful cutoffs or limits? finally, if i
> > am working with pre- and post-burn treatments, can these be viewed as
> > repeated measures DVs? also, are there any statistical techniques
> > that allow you to compare the variance explained with treatment
> > response ratios (standardized data)?
> >
> > thanks
> >
> > nate
> >
>
>
>
> --
> For personalized and experienced statistical consulting,
> visit www.statisticsdoc.com
>
>
>
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