Issue with small Sample Size and/or Power: One- way ANOVA HELP

Question

I am determining whether there is a significant difference in fruit quality across five locations (orchards) in WA state. I am making the assessment for five cultivars. Five quality indicators (Tannin, pH, TA, SSC, and SG), representative of fruit quality, were measured and only once per location per cultivar. More specifically, ~50 fruit were pressed and juiced into one composite sample and from this sample the indicators each measured once. I have data for three years, measurements repeated annually from 2012-2014. As I am again, determining whether there is a significant difference in fruit quality across Locations for each Cultivar separately, I attempted running a one-way ANOVA using Fit Model: inputting the five quality indicators in the Y role, Cultivar in the By role, and a Full Factorial of Year and Location in the Effects. As I am unfortunately missing data for some of the locations for varying years, I received a lot of 'lost DFs' errors and in testing the assumption of normality, Residuals by Cultivar, I observed that most of the data was not normally distributed, even after log transformation.

Given that there is missing data and only one data point per indicator per location per cultivar per year, is the data set a lost cause to analyze/sample size and power too small for me to make any confident conclusions at all, no matter the modifications? If not, anyone have suggestions for the errors?

Thank you very much

Steven_Moore · Answer

Travis,  It seems that you are at a dead end.  It appears that your data was not structured for meaningful analysis.  You can torture the data (i.e., transformations, etc.) until it "confesses,"  but you still end up with a confession under duress, and you know what that means. ;)

Until you are able to collect data under meaningful and structured conditions, all you have is "tribal knowledge" upon which to make conclusions.

travis_alexande · Answer

Hello,

We decided to compromise and count the years as replicates, so that we at least have a sample size of 3 rather than 1. Unfortunately, I still have the issue of the assumption of normality being rejected, even with any transformation. We will be conducting another year of data, so the sample size will increase while still small, but I was wondering if you had any other advice on what I could do for the normality if anything. Pasted below is some of my output. I worked with graph builder which was helpful, but my supervisor would like some ANOVA output for a report coming due, so I am in a bind.

Thank you again for all the help.

travis_alexande · Answer

Thank you for the input, much appreciated. I will definitely work with the graph builder. Missing data for an already small sample size, 1 datapoint per, limits my freedom greatly.