Can anyone provide me with an extensive explanation for which type of statistical tool should be used for:
1) Independent variables (Ethnicity): Chinese, Indian and Myanmar, code as 1, 2, 3.
2) Several dependent variables: TTCP, LCP, HCP, WCP, TCP (all are continuous data).
Initially, I used ANOVA to compare the difference in the MEANS for each DV among these ethnicities but found only LCP to be statistically significant in the overall ANOVA table. I then used it and proceeded to the post hoc test, while the rest of the DVs didn't show any significant difference. I think, I have to make a decision and conclusion without proceeding to the post hoc test since the overall ANOVA table shows no sig value, but I am not sure. What am I suppose to do in this case? Can I use MANOVA since I have several DVs? Which test is suitable for these problems?
For the above case, One-way ANOVA could be suitable since we have one single IV (Ethnicity) and Many DV (About five of them), after which we run post hoc multiple comparison test etc.
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