Hello Experts!
I have a set of 40 technologies and their corresponding adoption level. Also I have information various adoption barriers like market connectivity, finance and machinery. It is a quantitative rating data. For adoption level scale is 0-3 ( say 0%, 25 % , 50% and so on). Similarly for barriers it is 1-5 with some quantitative interpretation like 20% , 40% etc. For every technology 10-20 respondents have given their rating.
For every technology I want to see whether the adoption level is being influenced by any of the barriers. I am really confused as to how to compile all this data and make a meaningful sense out of it. Please suggest some good statistical method to move ahead. Will correspondence analysis work here ?
Dear Anjali,
Your technologies sound like a nominal data type - this is would be an independent grouping variable. It sounds like adoption level is your dependent variable. If the adoption level had been more accurately measured then you could have run a factorial ANOVA with adoption level as the scale dependent variable. If the respondents for each technology are the same then it would have been repeated measures. If they are different then it would have been independent measures. As it is, I would not recommend factorial ANOVA with such a coarse dependent variable.
Furthermore, with only 4 values for adoption level even non-parametric methods are going to struggle. You could only measure technology as your independent variable. If your measures are repeated you could have used Friedman ANOVA, if they were independent then you could have used Kruskal Wallis. The appropriate one of these might still be acceptable. However, these methods cannot take into account your other variables at the same time.
The technologies were assessed by a set of 20 respondents, hence , almost all or say 8-10 gave their response for different technologies (hence out of the same set, the number of respondents differ from technology to technology). My purpose is to see influence of 6 barriers on the adoption level. Could you suggest some relevant statistical tool for this? And will all the technologies be combined in the analysis, or a separate analysis will be run on each technology?
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