I am doing a research on the impact of social media on labour productivity, with LP broken into 3 categories. A questionnaire was administered to employees comprising of a mix of open-ended questions, as well as a 5-point Likert scale.
But I am at a loss with which statistical analysis to use to analyse the responses obtained.
Well you messed up by thinking of these as only one data analysis. Group the analyses by DV you wish to know about. Regression will work for you at that point. If your single DV is really categorical, with more than two categories you want multinomial logistic regression. If your single DV is really ordinal then you want ordinal logistic regression. Then group your IVs based on your research questions. At this point you build your regression models. Then google the type of regression you are using for each of these models along with your Statisical package. Now you should google instructions for running each model. If I have forgotten something see a really good regression professor or take the course. Your friend, David Booth
PS a good starting resource is Kutner, Applied Linear Statisical Models available in the z-library.
BTW if more than one DV per model this is a multivariate version of each of the above. In that case see the regression professor now. This is why a statistician says Proper Prior Planning Prevents Poor Performance. By that we mean plan for the analysis before you collect data. David Booth
Dear David,
if you look for a model to present the effect between dependent and independent variables. Try to use the ordinal logistic regression.
Regards
Multinomial logistic regression is appropriate for qualitative dependent variables with more than two categories
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