Kim,
In addition to the good advice you are/will be getting note that there is rarely only one way to do something. Also note may statistics are related to one another mathematically.
Dale
Dale Pietrzak, Ed.D., LPCMH, CCMHC
Director, Office of Academic Evaluation and Assessment
University of South Dakota
Slagle Hall Room 102
414 East Clark Street
605-677-6497
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Art Kendall
Sent: Wednesday, April 24, 2013 7:28 AM
To: [hidden email]
Subject: Re: Do I need to use a regression analysis?
Do you have a less coarse measurement of HR and Process?
Do you have the numerator and denominator from % of turnover as separate variables?
Ask your advisor what (s)he meant that you are calling "partial square modelling".
Art Kendall
Social Research Consultants
On 4/24/2013 7:15 AM, Kim S. [via SPSSX Discussion] wrote:
Hi Guys,
I have a question regarding my master thesis. In which I have 3 hypotheses.
H1= HR has a positive influence on Innovation
In which HR is a categorical variable existing out of low/medium/high
Innovation is a ratio/interval existing out of a % of turnover
H2=Process has a positive influence on Innovation
In which Process is a categorical variable existing out of low/medium/high
Innovation is a ratio/interval existing out of a % of turnover
H3= HR has a greater positive influence than Process on Innovation
The dataset exist out of 400 organizations, organizations can use both HR and Process, or just one of those. Not all organizations perform Innovation (but some do have HR or Process without Innovation)
I don't know yet if the data is normally distributed. And all variables also have "control variables".
In the book of Field i think I have to use Factorial Mixed ANOVA, according to my lectures notes i have to use a Multiple regression analysis and according to my mentor it could also be a partial square modelling? So now I am confused what to do and how to explain why I made this decision.
Hope to hear some from you, as it will help me out lots!
Best regards,
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Art Kendall
Social Research Consultants
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