I am conducting statistical tests for my current research project. Within the scope of this research project, I have two samples (divided by country clusters). The samples contain approximately 1500 entries each. The spoken languages differ within the samples but also across the samples.
- The first sample contains participants' responses and other variables from four countries (e.g. USA, UK) that are similar in their cultural dimensions, while
- The second sample contains participants' responses and other variables from four different countries (e.g. South Africa, Australia) than in the first sample.
I tried to choose the samples based on the fact that the cultural dimensions of these two samples are as different as possible. By choosing different countries for each sample, I tried to have independent samples. My independent variables are two cultural dimensions, while my dependent variables are:
- 2 categorical variables (excluded from the ANOVA because of the measurement scale requirement)
- 4 interval variables
My supervisor wants me to conduct tests on independence to be sure that the samples are independent of each other so that I can use an ANOVA (or another non-parametric equivalent) in the next step.
For the interval variables, I have already conducted Shapiro Wilks Tests as well as created histograms and GGQ plots. These showed a non-normal distribution. I also applied the Levene Tests that showed homogeneity for two out of the four interval variables.
However, to start with my actual analysis, I still need to find a way how to check the independence across samples. Thus, my question is:
Is it possible to conduct a Chi-Square Test for Independence on these two samples to find out whether they are independent or paired? I would run a Chi-Square Test for each dependent variable separately. Or is there another statistical test to determine whether my samples are statistically independent or paired?