of course, the typical software program, when doing regression analysis ...
prints out a summary ANOVA table ... so, there is one place to start ...
At 10:52 AM 12/11/01 -0500, Wuensch, Karl L wrote:
For a demonstration of the equivalence of regression and traditional ANOVA,
just point your
Jerry Dallal [EMAIL PROTECTED] wrote in sci.stat.edu:
It's lunch hour. I'm browsing. Shall I click on a link to a file
type that has the potential to carry viruses? OT1H, Karl is a
regular poster. OTOH, why run the risk? I guess I'll download and
look at it in WordView.
The file type was
It's lunch hour. I'm browsing. Shall I click on a link to a file
type that has the potential to carry viruses? OT1H, Karl is a
regular poster. OTOH, why run the risk? I guess I'll download and
look at it in WordView.
Wuensch, Karl L wrote:
For a demonstration of the equivalence of
Stan Brown wrote:
The file type was RTF. Unless I'm _VERY_ much mistaken, RTF cannot
carry macros of any sort, let alone viruses.
Oops, there is one loophole:
Yes, a loophole. In fact, one can embed a destructive program in a
pure ASCII file that can affect some machines. (Hint: it is
Hi
On Thu, 18 Oct 2001, Wouter Duyck wrote:
Suppose i have a factorial design with two between-subject factors (one
factor A of 3 levels and one factor B of 2 levels) en two within-subject
factors (one factor C of 2 levels and one factor D of 5 levels). Of course,
to perform an ANOVA on this
Rich Ulrich [EMAIL PROTECTED] wrote in message
news:[EMAIL PROTECTED]...
On Fri, 14 Sep 2001 16:44:11 + (UTC), Asst Professor
[EMAIL PROTECTED] wrote:
I have data from a 24 item (1-4 likert scale) survey for 5 groups with varying
Ns (9,16,23,34,43). According to the Levene
On Fri, 14 Sep 2001 16:44:11 + (UTC), Asst Professor
[EMAIL PROTECTED] wrote:
I have data from a 24 item (1-4 likert scale) survey for 5 groups with varying
Ns (9,16,23,34,43). According to the Levene homogeniety of variance test, I
also have varying means for some questions and not
Hi
On 29 May 2001, Alex Yu wrote:
Does anyone know any book/paper/website about teaching the relationship
between ANOVA and regression? I have Data Analysis for Research Designs
by Keppel. I also seached www.jstor.org but could not find anything.
I am interested in seeing what approaches
In article 9e9tkq$n1$[EMAIL PROTECTED],
Robert Dodier [EMAIL PROTECTED] wrote:
I wrote:
Mr. Eckmann is clearly thinking about the probability that
mean1 equals mean2, or the probability that mean1, ..., mean4 are
all equal. There is no reason to dissuade him from this; that the
machinery of
Thank you very much for your answer to my problem. Your explanation are
very clear precise. I wish I could have meet a professor in stats as
clear as you are during my high school education.
Sylvain Clement
At 14:19 09/02/2001 -0500, Donald Burrill wrote:
If for each Subject
Whether or not to use random effects should depend on whether you wish to generalize the results to some populations that the sample is (hopefully) representative of. Usually we wish to generalize to some population of subjects. Typically (but not neccesarily) we are not interested in generalizing
If for each Subject you have 4 Measures in each of the 3 Conditions, then
both Conditions and Measures are repeated-measures factors: you design
may be symbolized as S x C x M -- that is, Subjects (5 levels) are
crossed with both Conditions and Measures. This design is equivalent to
I may be wrong, but I thought that Gerhard was asking something like "If I
perform a linear regression but with a dichotomous dependent variable, do
I get 'garbage' results?"
Joseph
Gene Gallagher wrote:
In article [EMAIL PROTECTED],
Gerhard Luecke [EMAIL PROTECTED] wrote:
Can anyone
In article [EMAIL PROTECTED],
Joseph McDonnell [EMAIL PROTECTED] wrote:
I may be wrong, but I thought that Gerhard was asking something like "If I
perform a linear regression but with a dichotomous dependent variable, do
I get 'garbage' results?"
The results must be at least partly garbage. We
On Mon, 06 Nov 2000 18:36:16 +0100, Joseph McDonnell
[EMAIL PROTECTED] wrote:
Gentlemen,
I agree with both of you. Several correspondents had already pointed out that a
logistic regression approach would be more appropriate in this situation.
However, I was trying to steer the discussion
In article [EMAIL PROTECTED],
Gerhard Luecke [EMAIL PROTECTED] wrote:
Can anyone name some references where the problem of using a
DICHOTOMOUS
variable as a DEPENDENT variable in an ANOVA is discussed?
Many thanks in advance,
Gerhard Luecke
Check out Ramsey Schaefer's "The Statistical
Gerhard Luecke wrote:
Can anyone name some references where the problem of using a DICHOTOMOUS
variable as a DEPENDENT variable in an ANOVA is discussed?
Many thanks in advance,
Gerhard Luecke
Such analyses may be done using either logistic regression methods or
generalized estimating
Gerhard Luecke wrote:
Can anyone name some references where the problem of using a DICHOTOMOUS
variable as a DEPENDENT variable in an ANOVA is discussed?
Many thanks in advance,
Gerhard Luecke
I'd first try logistic regression. If all your variables
are categorical, you can look at some
On 24 Sep 2000 23:30:57 -0700, [EMAIL PROTECTED] (Beng Hai Chea)
wrote:
I have a very basic ANOVA question regarding transformed variable.
Example: I have 6 different types of habitats and I have obtained 25
readings from each of the different type of habitats. After doing the ANOVA
I have a very basic ANOVA question regarding transformed variable.
Example: I have 6 different types of habitats and I have obtained 25
readings from each of the different type of habitats. After doing the
ANOVA
procedure, I discovered that non-constant error variance is present.
On Thu, 22 Jun 2000, Alex Yu wrote (slightly edited):
ANOVA is said to be robust against assumption violations when the
sample size is large. However, when the sample size is huge, it tends
to overpower the test and thus the null may be falsely rejected.
Which is a lesser evil? Your
It rather sounds as though data are already in hand, rather than yet to
be collected. That being the case, as I shall assume, your 2nd model has
half the data that your 1st model has, and it is not clear whether this
reflects the discarding of half the available data, or the averaging
Bill said earlier:
Yes, we do this so that we will have examples of all combinations of x1
and
x2,as we would do when using a factorial anova design. But such uniform
sampling does not make the variables into causes, Adding x1 to x2 causes
y,
Gus responded:
Here you are using a very
William Chambers wrote:
Gus,
You are making a defense of studying distributions as they are thrown at us
by nature/circumstances, This seem the way to go to social scientists
because we tend to believe that our causes are embedded in all sorts of
complex interactions and can not be
Gus said:
Here is how I interpret what you've said to date:
1. If you take two uniformly distributed random variables x1 and x2 and
form
the sum y = x1 + x2, then y has a distribution that is not uniform.
2. If you have two variables x and y and want to determine whether x
depends
on y or
Guss said:
No. You said yourself that you are _selecting_ the x1 and x2 to be
uniform.
Yes, we do this so that we will have examples of all combinations of x1 and
x2,as we would do when using a factorial anova design. But such uniform
sampling does not make the variables into causes, Adding
Gus,
You are making a defense of studying distributions as they are thrown at us
by nature/circumstances, This seem the way to go to social scientists
because we tend to believe that our causes are embedded in all sorts of
complex interactions and can not be isolated from their context, If we
On 10 Feb 2000, Richard M. Barton wrote:
--- Alex Yu wrote:
A statistical procedure alone cannot determine casual relationships.
---
Correct. A lot depends on eye contact.
rb
And also, at least 2 statistical procedures are required...
At 12:40 PM 2/10/00 +, sofyan2000 wrote:
Is there a statistical test in ANOVA / MANOVA that can show the causal
direction between 2 variables (Independent and Dependent).
i don't think so ... this is determined (if it can be at all) by the DESIGN
of the investigation ... and what you did
A statistical procedure alone cannot determine casual relationships.
Rather it involves the design and measurement issues. The following is
extracted from my handout:
One of the objectives of conducting experiments is to make causal
inferences. At least three criteria need to be fulfilled to
--- Alex Yu wrote:
A statistical procedure alone cannot determine casual relationships.
---
Correct. A lot depends on eye contact.
rb
===
This list is open to everyone. Occasionally, people lacking respect
for
sofyan2000 wrote:
Is there a statistical test in ANOVA / MANOVA that can show the causal
direction between 2 variables (Independent and Dependent).
In short, no.
In more detail, causal inference is dependent on the design you used,
not
the statistical technique applied to the data. If you
hmmm. what is variance-between groups when all of them are standardized?
am I missing something?
- Original Message -
From: haytham siala [EMAIL PROTECTED]
To: [EMAIL PROTECTED]
Sent: Wednesday, February 09, 2000 5:12 PM
Subject: ANOVA data
Can I perform an ANOVA on standardized
- Original Message -
From: haytham siala [EMAIL PROTECTED]
To: [EMAIL PROTECTED]
Sent: Wednesday, February 09, 2000 2:12 PM
Subject: ANOVA data
Can I perform an ANOVA on standardized variables?
---
If you
sofyan2000 wrote:
I have conducted a repeated measure mixed two-factor ANOVA on one sample
consisting of 2 groups (conservatives and liberals). The dependent variables
where ATTA (attitude towards policy A) and ATTB (attitude towardfs B). I
have a few questions:
1. What statistical ANOVA
On Mon, 7 Feb 2000 18:42:03 -, "sofyan2000"
[EMAIL PROTECTED] wrote:
3. Which part of the SPSS results (which heading?) afer running an MANOVA
shows the interaction between the between groups IV (political category
conservative vs. liberals) and the within-groups DV (ATTA ATTB).
In sci.stat.consult sofyan2000 [EMAIL PROTECTED] wrote:
: I have conducted a repeated measure mixed two-factor ANOVA on one sample
you shouldn't have
: 1. What statistical ANOVA test can reveal an outlier in my data?
none
: 2. If my test failed the 'homogeneity of variance/ covariance' test,
On Sat, 5 Feb 2000 16:46:38 -, "haytham siala"
[EMAIL PROTECTED] wrote:
Is the homogoneity of variance-covariance prerequisite to ANOVA a
requirement?
No, it is a warning that your model might be inappropriate, in any of
several ways. A single EXTREME outlier could make any average
On 14 Dec 1999 08:40:18 -0800, [EMAIL PROTECTED] (William B. Ware)
wrote:
As I recall, there was an article by Lunney et al that appeared in the
Journal of Educational Measurement that examined the use of ANOVA with "1"
and "0" as the DV. I believe that they concluded that distortion was
On 14 Dec 1999 16:38:00 -0800, [EMAIL PROTECTED] (Rich Strauss)
wrote:
snip
I'll just add the usual caveat that hasn't yet been mentioned in these
responses about proportions: the transformations, use of the binomial, and
comment about proportions just being means all assume that the data
On Tue, 14 Dec 1999, Wouter Duyck wrote:
I have a question. I have n subjects. For each subject, I have a
proportion. I want to test if there are some differences in that
proportion, depending on some independent variables (e.g. sex) on which
the subjects differ.
Can I use those
___
On Tue, 14 Dec 1999, Robert Dawson wrote:
- Original Message -
From: Donald F. Burrill [EMAIL PROTECTED]
To: Wouter Duyck [EMAIL PROTECTED]
Cc: [EMAIL PROTECTED]
Sent: Tuesday, December 14, 1999 9:03 AM
Subject: Re: ANOVA with proportions
On Tue, 14 Dec 1999, Wouter D
In article [EMAIL PROTECTED],
Wouter Duyck [EMAIL PROTECTED] wrote:
Hi to all...
i have a question. I have n subjects. for each subject, i have a
proportion. i wanna test if there are some differences in that
proportion, depending on some independent variables (e.g. sexe) on
wich
the
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