Frankfoot
2012-Jun-02 12:56 UTC
[R] Compare data between two groups/countries on 5-point Likert scale questionnare?
Hi everyone, I'm stuck on my dissertation which is due next week. I'm a business major student and my project is a comparative research on corporate social responsibility (CSR) between Chinese and German firms. According to my literature review, it's quite obvious that German firms have much better CSR initiatives and strategies than the Chinese ones and I wanted to test whether it was true by sending out Likert-scale questionnaires to Chinese and German firms through bankers in my family. I have already got 24 responses from the Chinese and 27 from the Germans and it looked quite evident that the hypothesis is correct. Now that I am writing my analysis chapter, I am lost as I don't know which is the best way to analyse my data after trying to find a solution for days. Basically, my questionnaire is structured in this way: Q1 - Q5: statements on environment-oriented CSR Q6 - Q10: statements on workplace-oriented CSR Q11 - Q15: statements on community-oriented CSR Q16-Q20: statements on market-oriented CSR All of the statements are 5-pt Likert questions. I initially planed to compare the grouped mean values for each of the above section but I know that it's not scientific. So can someone give me any advice on which kind of tests is most suitable for my research? As you can see, my sample size is quite small. I really appreciate your time! -- View this message in context: http://r.789695.n4.nabble.com/Compare-data-between-two-groups-countries-on-5-point-Likert-scale-questionnare-tp4632163.html Sent from the R help mailing list archive at Nabble.com.
Uwe Ligges
2012-Jun-03 15:07 UTC
[R] Compare data between two groups/countries on 5-point Likert scale questionnare?
This is the R-help mailing list. It is not a statistical consulting list nor the "others write my thesis" list. On 02.06.2012 14:56, Frankfoot wrote:> Hi everyone, I'm stuck on my dissertation which is due next week.Interesting. The question given below should arise two years before the dissertation is due (actually, at the time when you planned the questionnaire). Otherwise I'm interested to hear which university accepts theses where the analysis chapters can be written within a week and the evaluation and analysis of questionnaires is not planned in advance. Uwe Ligges > I'm a> business major student and my project is a comparative research on corporate > social responsibility (CSR) between Chinese and German firms. According to > my literature review, it's quite obvious that German firms have much better > CSR initiatives and strategies than the Chinese ones and I wanted to test > whether it was true by sending out Likert-scale questionnaires to Chinese > and German firms through bankers in my family. I have already got 24 > responses from the Chinese and 27 from the Germans and it looked quite > evident that the hypothesis is correct. Now that I am writing my analysis > chapter, I am lost as I don't know which is the best way to analyse my data > after trying to find a solution for days. Basically, my questionnaire is > structured in this way: > > Q1 - Q5: statements on environment-oriented CSR > Q6 - Q10: statements on workplace-oriented CSR > Q11 - Q15: statements on community-oriented CSR > Q16-Q20: statements on market-oriented CSR > > All of the statements are 5-pt Likert questions. I initially planed to > compare the grouped mean values for each of the above section but I know > that it's not scientific. So can someone give me any advice on which kind of > tests is most suitable for my research? As you can see, my sample size is > quite small. I really appreciate your time! > > -- > View this message in context: http://r.789695.n4.nabble.com/Compare-data-between-two-groups-countries-on-5-point-Likert-scale-questionnare-tp4632163.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.