Hi Michael:
Be careful with the effect size statistic that G*Power uses, sometimes
it is using rho. rho = .3 would be a medium effect size.
Ken
PS - It is surprising how underpowered are many of the experiments
reported in the journals.
------------------------------------------------------------------------
Kenneth M. Steele, Ph. D. [email protected]
Professor
Department of Psychology http://www.psych.appstate.edu
Appalachian State University
Boone, NC 28608
USA
------------------------------------------------------------------------
On 8/27/2013 9:59 AM, Michael Britt wrote:
Also helpful. So, to answer my own previous question, based on what they
found in the correlational study and what one might guess from previous
research, I'm going to assume that the effect size here, if it exists,
is probably small. So I used .3 in G*Power. The result? G*Power suggests
that I get 242 subjects per group. These researchers had 26 subjects in
each group.
So: if you were the reviewer what would you conclude? The researchers found:
"...the results revealed that participants in the anthropomorphism
condition were tendentially less willing to help the victims of the
natural disaster (M = 4.39, SD = 1.02) than participants in the control
condition (M = 4.89, SD = 0.87), t(50) = –1.91, p = .06, d = 0.53.
Would you recommend that they get more subjects?
Michael
Michael A. Britt, Ph.D.
[email protected] <mailto:[email protected]>
http://www.ThePsychFiles.com
Twitter: @mbritt
On Aug 27, 2013, at 8:59 AM, Stuart McKelvie <[email protected]
<mailto:[email protected]>> wrote:
Dear Tipsters,
There are various ways to plan sample size. When teaching this in
research methods, I divide the issues into two parts:
1. Estimation of population values.
Here, more is better but there are diminishing returns. Think of the
fact that we rarely see more than 1500 people in national polls and
surveys. The formula is based on minimizing standard error. Of course,
sampling is critical.
2. Conducting studies with variables: experimental, subject or
correlational.
There are four interconnected concepts: effect size, alpha, power and
sample size. When any three are known, the fourth is determined. You
can decide where to set alpha and power. For effect size (d), you can
be guided by Cohen's guidelines for small, medium and large (.3, .5,
.8) and choose the value you are looking for. This may come from past
research or, in its absence, what you think is interesting
theoretically or practically.
Cohen's book on power analysis gives tables where you can look up the
sample size needed after specifying the values you choose. There is
also this webiste:
http://homepage.stat.uiowa.edu/~rlenth/Power/
Sincerely,
Stuart
_____________________________________________________
Sent via Web Access
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"Recti cultus pectora roborant"
Stuart J. McKelvie, Ph.D., Phone: 819 822 9600 x 2402
Department of Psychology, Fax: 819 822 9661
Bishop's University,
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" Floreat Labore"
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------------------------------------------------------------------------
*From:*Paul C Bernhardt [[email protected]
<mailto:[email protected]>]
*Sent:*27 August 2013 08:41
*To:*Teaching in the Psychological Sciences (TIPS)
*Subject:*Re: [tips] Sample Size: How to Determine it?
There is software to determine this. One excellent and free app is
G*Power.
http://www.psycho.uni-duesseldorf.de/abteilungen/aap/gpower3/
I would use the correlational study to give me an estimate of effect
size. As you describe, I would use that in the software to estimate my
number of participants to attain the desired power. Practicality
constraints on number of available participants usually limits things.
I did such an estimate using G*Power a few weeks ago for a study we
are planning. We will need to collect data over two semesters because
the anticipated number of participants available from one semester's
worth of students would only give us power of about .66, whereas two
semester's worth would bump us up over .90.
Paul
On Aug 27, 2013, at 8:18 AM, Michael Britt wrote:
I'm reading an interesting piece of research on anthropomorphism
which essentially states after a natural disaster if we use the term
"mother nature" when describing it, people will be less willing to
contribute to relief efforts ("Humanizing nature could help the
perceiver to conceive natural events as imbued with intentionality
and significance rather than considering them merely random and
meaningless phenomena"). They did two studies. Here's the issue/question:
* Study 1 was correlational and involved 96 students. The results
were supportive at <.001
* Study 2 was an experiment (no need to go into the details)
involving 56 students. The results were, in the authors words,
"tangentially" supportive with p<.06
I think the study was well conducted so I don't mean to slight the
researchers. My guess is that if they used more subjects they
probably would have reached p<.05 - but would that have been an
example of "selective stopping"? I assume it would be.
So how exactly does a researcher determine beforehand - as we are
suggesting they do - the number of subjects they ought to try to get
for the study? I'm just not familiar with the process. Does one look
at the effect sizes of previous related studies to determine if the
effect is large or small and then make a decision? But let's say the
effect is assumed to be small, so do you use 100 subjects? 500? How
is this number determined?
Appreciate the insight in this.
Michael
Michael A. Britt, Ph.D.
[email protected] <mailto:[email protected]>
http://www.ThePsychFiles.com
Twitter: @mbritt
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