Taking a break from grading papers...
One website sites p183 of Ramachandran V. S. & Blakeslee S. (1998)
Phantoms in the Brain: Probing the Mysteries of the Human Mind. New York:
Morrow & Co for this quote...
http://cns-alumni.bu.edu/pub/slehar/quotes/rama.html but, this is most
likely just w
Is there any evidence that attributes the phrase to either Parker or
James?
Charles M. Huffman, Ph.D.
Chair, Psychology Department
Cumberland College, Box 7990
Williamsburg, KY 40769
-Original Message-
From: Robin Pearce [mailto:rpearce@;
On 13 Nov 2002 at 0:28, I wrote:
> I'm betting on James over Parker. He was probably sniffing ether at the time. But
>where did he say it?
No, actually, I think he really _was_ on ether at the time. But I don't know how I
know this.
Stephen
On 12 Nov 2002 at 21:49, Robin Pearce wrote:
>
> Actually, I don't know where the rumor about William James got started.
> The poem is by Dorothy Parker. (The first stanza, that is.)
>
Well, it's all over the Internet and always attributed to James. Curiously, though,
the only specific source
Of course, you could continue to add additional parameters that affect
power, such as the relative efficiency of the estimator that you employ, the
correlations between samples in nonindependent samples designs, the exact
shape of the distributions from which the samples were drawn, the
reliability
I think Mike meant to say that p is only meaningful if you remember that it
is conditionalized upon the null being true. Even if the null is never or
almost never true, p as an abstract quantity can be meaningful, just like a
sampling distribution is a meaningful thing even if it is never obtained
Actually, I don't know where the rumor about William James got started.
The poem is by Dorothy Parker. (The first stanza, that is.)
Nice sequel.
**
Robin Pearce Abrahams
Boston University
[EMAIL PROTECTED]
On Tue, 12 Nov 2002, Dav
William
James scribbled down the Great Thought that had appeared in his
dream.
He later found he had written:
Higamous, hogamous, woman's monogamous.
Hogamous, higamous, men are polygamous. *
This morning I found this on the notepad by my bed:
Higamous, hogamus, alpha's dichotomous.
Mike, could you expand on how it is that a p-value is
only meaningful if the Null is true? I understand the
second part of your statement (Replication only useful
is Null is rejected)... but would like more info on
the first...
cheers!
Jean-Marc
--- Mike Scoles <[EMAIL PROTECTED]> wrote: >
A
Earlier today I wrote:
> Power is a funtion of two independent components: effects size and sample size
> (suitably adjusted depending on the design).
This was, of course, not quite correct. Power is a function of *three* independent
components: effect size, sample size, and *alpha* (the probabil
Any of you folks have an Atari 850 interface in you attic? I have been looking on ebay and other places
---
You are currently subscribed to tips as: [EMAIL PROTECTED]
To unsubscribe send a blank email to [EMAIL PROTECTED]
A p-value is only meaningful if the null hypothesis is true. Replication is
only meaningful if the null is false. I would be interested in the
reference to calculating the probability of replication given p.
> -Original Message-
> From: Martin J. Bourgeois [mailto:MartyB@;uwyo.edu]
> Se
Maybe I should quit before I get too far behind, but what I'm trying to
say (and apparently failing) is that an observed difference between
means is more likely to be replicated when the p is .001 than when the p
is .1. You can certainly calculate the probability of replicating a
result with a give
Note that what Cohen is questioning is not a particular practice of
hypothesis testing, but the more basic assumption of the null
hypothesis as a useful construct.
Here I would agree!
At 10:00 AM -0500 11/12/02, Christopher D. Green wrote:
"Martin J. Bourgeois" wrote:
I like that advice. I al
At 11:45 PM -0500 11/11/02, Karl L. Wuensch wrote:
Last I checked, the significance level, p, was a probability (the
conditional probability of obtaining results as more discrepant with the
null than are those in the current sample), and probabilities vary
CONTINUOUSLY from 0 to 1. At least that
At 9:27 AM -0700 11/12/02, Martin J. Bourgeois wrote:
I think you misunderstood me. I don't think that the probability of
replicating a p of .001 is .001, but the probability of replicating a p
of .001 is certainly much greater than the probability of replicating a
p of .1, which is what I said.
Wuensch, Karl L wrote:
> Better to find power for the smallest effect that you would consider not to be
>trivial in
> magnitude. If that power is high, then you can make a strong statement
> regardless of whether your effect is "statistically significant" or not.
Well, yes, but the sta
I think you misunderstood me. I don't think that the probability of
replicating a p of .001 is .001, but the probability of replicating a p
of .001 is certainly much greater than the probability of replicating a
p of .1, which is what I said.
Marty
-Original Message-
From: Christopher D.
...and while I'm recommending accessible (both physically and cognitively) Cohen
articles, check this one out as well:
Cohen, J. (1990). Things I Have Learned (So Far). American Psychologist, 45 (12),
1304-1312.
ABSTRACT
This is an account of what I have learned (so far) about the application o
Gene,
The reference you are looking for is
Merritt, C.B., & Fowler, R.G. (1948). The pecuniary honesty of the public at large. Journal of Abnormal and Social Psychology, 43, 90-93.
Susan Sheffer, Ph.D.
Department of Psychology
Lewis University, x5602
[EMAIL PROTECTED]
[EMAIL PROTECTED]
In a me
"Martin J. Bourgeois" wrote:
> I like that advice. I also like to think of p's as measures of
> reliability; a p of .001 is more likely to be replicated than a p of .1,
> given the same effect size.
You shouldn't. As Jacob Cohen wrote in the article previously recommended (a
recommendation with w
Annette Taylor wrote:
> I don't think you can calculate power--I recall doing power calculations for my
> dissertation--the last time I thought that was a good use of my time! But you
> can certainly ask SPSS to calculate effect size, and that is, in my mind, a
> sufficient approximation.
I don'
I second the suggestion to use a program other than SPSS (such as the free
G*Power) to do the power analysis. SPSS may compute power using an
unreasonable assumption -- that the actual effect in the population is of
the same magnitude as the observed effect in the sample. Better to find
power for
This is one of the aggravating things about spss; it won't do effect
sizes and power for the one way anova, but it will do them for the
univariate GLM (which is identical to one way anova when you have one
IV).
-Original Message-
From: Dennis Goff [mailto:dgoff@;rmwc.edu]
Sent: Tuesday, N
I like that advice. I also like to think of p's as measures of
reliability; a p of .001 is more likely to be replicated than a p of .1,
given the same effect size.
Marty Bourgeois
University of Wyoming
-Original Message-
From: Karl L. Wuensch [mailto:wuenschk@;mail.ecu.edu]
Sent: Monday
I don't think you can calculate power--I recall doing power calculations
for my dissertation--the last time I thought that was a good use of my
time! But you can certainly ask SPSS to calculate effect size, and that
is, in my mind, a sufficient approximation.
Annette
On Tue, 12 Nov 2002, Paul Sm
I agree that the significance level is continuous, and yes, probabilities
range from 0 to 1. But, the decision of whether something is statistically
significant still seems like an either/or situation. I guess it depends on
how you phase the question: Is the question "how likely is it?" Or is th
Dear Rob,
In SPSS 11.0 it is possible to calculate the estimated power for ANOVAs.
I have not tried this for a one-way ANOVA however.
>From the Help guide for "GLM Univariate Options..."
"Display...Select Observed power to obtain the power of the test when
the alternative hypothesis is set based
Rob,
I don't think that the one-way procedure will calculate power for her. However, if you
have General Linear Model procedure she can use the univariate procedure to conduct
her one-way ANOVA (it sets up the same way as the one-way) and simply request effect
size and observed power from the o
Stuart Vyse wrote:
> I believe it was Jacob Cohen who wrote, "God loves .06 just as much as
.05."
As well as this must-read article on the topic:
Cohen, J. (1994). The earth is round (p < .05). American Psychologist, 49,
997-1003.
Paul Smith
Alverno College
Milwaukee
---
You are currently
I believe it was Jacob Cohen who wrote, "God loves .06 just as much as .05."
--
Stuart A. Vyse, PhD | Department of Psychology | Phone: 860-439-2339
Associate Professor | Connecticut College | FAX: 860-439-5300
| New London, CT 06320 |
---
You are c
Hazarding an educated but perhaps incorrect response...
I don't think that she's going to be able to calculate power using SPSS.
SPSS is a program for working with actual data, and power is a calculation
based on a number of assumptions that one makes about the data (most
importantly, hypothes
First, I'd like to thank everyone who responded to the list yesterday with
comments and suggestions for my student (re: marginally significant).
It seems as though the most prudent step is to have her calculate the power.
We have SPSS v.11.0 on campus and I have been encouraging students to use
th
33 matches
Mail list logo
