She would like to know the effectiveness of different HIV prevention programs on adolescences’’ sexual practices. I am working through another scenario and have a question:ĭr. Thanks for your cooperation as I await your response. How do I proceed from here? What can I do to achieve this goal of meeting all assumptions of ANOVA? However, with ANOVA I am faced with the challenge of violation of assumption of sample size for the groups being greater than 10, as I have a sample size of 5 replicates for 15 of the 16 species and 4 replicates for 1 of the 16 species. Log transformation of data had no effect on the outcome of equal variances as both the Box test and Levene’s test were still significant. I initially wanted to use MANOVA for testing differences between mean concentrations of each of the 4 heavy metals across the 16 different species being investigated but several assumptions of MANOVA especially homogeneity of variance and sample size were violated.
I also have 4 dependent variables(4 different heavy metals).
I have one independent variable called “Plant Specie” with 16 levels(16 different species) and each level(specie) has 5 replicates. I am at a critical point in my journey to a PhD and I really need urgent guidance and cross-checking of statistical methods, so I do not waste time and start all over again with my stats analyses, so please respond to meĬurrently I have a challenge and it is with violated assumptions of M/ANOVA. Your resources have been so helpful to me and have guided me so far in improving my understanding of statistics and statistical methods. Is having a post hoc test with simultaneous CI of 95% enough, even when I do an omnibus test with a=0.05? Or do I do an alpha correction (let’s say the Bonferroni correction for example, which will give a corrected alpha of 0.005) and apply that corrected alpha to my omnibus test, before proceeding with my post hoc test with simultaneous CI of 95%? Am I on the right track with my decision? Or do you advice me to use the classic one-way ANOVA or Welch’s ANOVA instead? If the classic one-way ANOVA is applicable, I plan to run Hsu’s MCB instead as my post hoc test, as I see it more powerful in this case compared to Tukey’s HSD.Īnother question I have is regarding the FWER, because I believe that having 5 groups will cause alpha inflation (my target alpha is 0.05). I remember being adviced that Brown-Forsythe F* leads to more valid results that Welch’s ANOVA when the sample size per group is incredibly small such as that lower than 7, so I plan to use it, along with Games-Howell. As such, I plan instead to conduct Welch’s ANOVA or Brown-Forsythe F*. The thing is I can only have 3 scores as my sample size per group and I cannot increase it anymore due to certain constraints.
The significantly small sample size concerns me as I believe this will certainly affect the validity due to a highly likely unequal variances. My sample size within one group is 3 and this is the same for all groups.
However, I am concerned that my sample size is too small. As such, I planned to conduct one-way ANOVA to identify equality in all means. I plan to propose conducting an experiment with 5 independent samples. If you do not mind, I would like to humbly ask for your advice.
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