Hi

I think that the Principal component analysis method could help you!

for more details, you can visit the link:

https://en.wikipedia.org/wiki/Principal_component_analysis

I suppose different crops were used between years. Could one not consider the years to be an addition between factor? If so, one would end up with a 2 (years, between) x 3 (dates, between) x 3 (varieties, between) x 4 (times, within) design.

Respected Dr. R. Hadria

Thank you for your suggestions.

But Principal component Analysis is somewhat similar to factor analysis (a data reduction technique), where a large number of variables with too large number of observations which are hard to study and interpret properly are reduce to a few variables in a more meaningful form. Even the Extraction Method used by SPSS in Factor analysis is: Principal Component Analysis.

It is generally applied in Genetic and plant breeding studies where experiment is conducted to test a number of traits/characters from wider gene pools.

I was concerned about the statistical analysis of simple growth, yield and phonological observations that are generally taken by Agro-meteorologists and Agronomists during their repeated trials over the years.

Respected Jos Feys Sir

The combination {2 (years, between) x 3 (dates, between) x 3 (varieties, between) x 4 (times, within) design} is still applicable if the same crop is used next year in the repeated trial.

Thanks for the suggestion brother Behzad Rouhanizadeh

I'll look into that.

it's very easy, you can use excel spreadsheet. i can send you (next week) an exemple in excel in which you can introduce your data and resolve your question.

regards

Thank You HAMIMED Abderrahmane sir, that would be of much help.

Hi,

Please find attached the ANOVA split plot exemple (split_plot.xlsx) in excel spreadsheet.

The input data are n blue colour.

regards.

Hamimed

Hi,

I think that the easiest way is to do first an ANOVA year by year and in a second step to do an combined ANOVA (not just a polled one).

Regards

Ciré

Respected HAMIMED Abderrahmane Sir

Thank you for sharing the Spreadsheet, but it is showing the variance within one year.I am acquainted with that as i have followed the same approach during the analysis of My Master’s degree research (the field trial was of one year).

I’ve asked about analyzing the data of repeated field trials (of more than 1 year) without simply following the traditional approach of pooling the data of 2 or more, and then analyzing, but keeping 'year' as one of the additional factor as you have taken varieties (Factor 1) and dates of sowing (Factor 2) in the spreadsheet.

I May be wrong but practically, polled analysis sometimes doesn’t sounds appropriate because, there isn’t any surety, whether the data from previous year trials will synchronize significantly with the current year or not. There can be some spatial and temporal variations in the data (that may probably surpass 5 % level of significance, what we usually follow in our statistical analysis) even if the same crop is sown on the same piece of land.

see this link:

https://www.researchgate.net/post/How_do_I_analyze_a_split-plot_three-way_factorial_design_in_SAS_R_or_both

If exactly the same individual crops maybe with an ID number of code) were used in the 2 years, one would end up with a 3 (dates, between) x 3 (varieties, between) x 2 (years,within) x 4 (times, within) design. A design with 2 between factors and 2 within (doubly repeated) factors.

Genstat can easily do that