bject:=
Re: [ECOLOG-L] Dealing with non-normal, ordinal data for 2-way ANOVA with =
interactions=0A=0A=0A>You seem a trifle sensitive about models and modeling=
- statistics =0A>are just tools.=0A=0AFully agree..but these tools tha=
t have to be applied correctly.=0A=0A> It makes no sen
>You seem a trifle sensitive about models and modeling - statistics
>are just tools.
Fully agree..but these tools that have to be applied correctly.
> It makes no sense to say that something is wrong with the data.
I see data sets all the time that are wrong; mistakes, typos, wrong
coding
Bahram Momen wrote:
> Highland Statistics Ltd. wrote:
>
>> >Date:Mon, 12 Mar 2007 15:35:18 -0700
>> >From:John Gerlach <[EMAIL PROTECTED]>
>> >Subject: Re: Dealing with non-normal, ordinal data for 2-way ANOVA
>> with interactions
&
I agree completely with the tool analogy and with using the correct tool fo=
r the data. As I mentioned before, the scale of the data is not always obvi=
ous after you have run the experiment. Do you analyze population size data =
inflated with zeros as a continuous or a bivariate response data?=0A
Statistics are just tools. Using the best tool for the job is what's
being discussed here.
If a statistical technique is more powerful than another, models the
data on it's natural scale, and can do all of the things ANOVA can do
why not use it. That would, at least to me, seem a much more ef
Highland Statistics Ltd. wrote:
> >Date:Mon, 12 Mar 2007 15:35:18 -0700
> >From:John Gerlach <[EMAIL PROTECTED]>
> >Subject: Re: Dealing with non-normal, ordinal data for 2-way ANOVA
> with interactions
>
> >My short answer is that for controlled
You seem a trifle sensitive about models and modeling - statistics are just=
tools. Nearly every modern text book clearly points out that ANOVA, regres=
sion, etc are specific applications of a general mathematical approach but =
that each is a tool designed for a particular purpose. So, yes they
>Date:Mon, 12 Mar 2007 15:35:18 -0700
>From:John Gerlach <[EMAIL PROTECTED]>
>Subject: Re: Dealing with non-normal, ordinal data for 2-way ANOVA
with interactions
>My short answer is that for controlled blocked factorial experiments where =
>interactions are im
seems to be the most ef=
ficient.=0A=0A=0A- Original Message =0AFrom: Swalker <[EMAIL PROTECTED]
COM>=0ATo: [EMAIL PROTECTED]: Monday, March 12, 2007 11:30:3=
9 AM=0ASubject: Re: [ECOLOG-L] Dealing with non-normal, ordinal data for 2-=
way ANOVA with interactions=0A=0A=0AThis is an
e ----
>> From: Highland Statistics Ltd. <[EMAIL PROTECTED]>
>> To: ECOLOG-L@LISTSERV.UMD.EDU
>> Sent: Sunday, March 11, 2007 4:38:10 AM
>> Subject: Re: [ECOLOG-L] Dealing with non-normal, ordinal data for
>> 2-way ANOVA with interactions
>>
>&g
ata - failure time approaches don't lend themselves
>to factorial ANOVA.
>
>John Gerlach
>
>
>
>- Original Message
>From: Highland Statistics Ltd. <[EMAIL PROTECTED]>
>To: ECOLOG-L@LISTSERV.UMD.EDU
>Sent: Sunday, March 11, 2007 4:38:10 AM
>Su
TED]
Sent: Saturday, March 10, 2007 6:06 AM
To: ECOLOG-L@LISTSERV.UMD.EDU
Subject: Re: [ECOLOG-L] Dealing with non-normal, ordinal data for 2-way
ANOVA with interactions
You might also consider permutation-test based ANOVA, which eliminates
any need for normality. See the book "Randomization
On Wed, 7 Mar 2007 16:19:31 -0500, Ryan Earley <[EMAIL PROTECTED]>
wrote:
>Help with stubbornly non-normal data
>
>We have a data set with 2 independent variables and 1 dependent (Gosner
>stage for amphibian larvae).
Hello,
Normality is less important. What about homogeneity?
We have tried
You might also consider permutation-test based ANOVA, which eliminates
any need for normality. See the book "Randomization, Bootstrap and
Monte Carlo Methods in Biology" By Bryan F. J. Manly, which has a
section on this. A two-factorial model is implemented in the program
MeV (www.tm4.org), but thi
Well - opinions vary on this topic, but, a couple of things to consider in
2-way factorial ANOVA with a non-normal response.
1) ANOVA is robust with respect to deviations from normality, especially
with decent sample sizes. (Good ole Central Limit Theorem comes in handy!)
So, what is your sample
Help with stubbornly non-normal data
We have a data set with 2 independent variables and 1 dependent (Gosner
stage for amphibian larvae). We have tried every creative way to transform
the data and end up with significant deviation from normality each time.
What we'd like to ultimately do is t
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