Thanks  Paul.  I've downloaded G*Power.  Question: the correlational component 
of the study revealed r = -.21, p<04 (higher tendency to humanize nature were 
associated with a lower tendency to help victims of a natural disaster).  The 
next test will be an independent samples t-test.

How does this info help me enter the values needed by G*Power: "Effect Size d" 
and "Allocation ratio N2/N1"?

Michael

Michael A. Britt, Ph.D.
[email protected]
http://www.ThePsychFiles.com
Twitter: @mbritt

On Aug 27, 2013, at 8:41 AM, Paul C Bernhardt <[email protected]> wrote:

>  
> 
>  
> 
>  
> 
> 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]
>> http://www.ThePsychFiles.com
>> Twitter: @mbritt
>> 
>> 
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