Analyse Seasonal Summaries

This dialog analyses the seasonal summaries added to the trial by the Add Seasonal Summaries menu. You need to select the column type whose seasonal summaries are to be produced and specify output that you want. The output settings for the seasonal summaries will be those last used in the Trial Analysis dialog. This menu also saves the results automatically to Word and Excel files in the current working directory. The file names are formed from the trial Id with the text ” SeasonalSummary” and file type (.rtf or .xlsx) appended. The summary produces a table of results for each year and, if the trial has more than one year, averages over the years and totals in each year. If Relative means has been selected in the Trial Analysis menu, a second page of relative results is produced for each page in the original summary.

Analyse columns of type

Select the column types from the drop-down list that you want to be analysed.

Include LSI limits in spreadsheet

If this item is ticked, the SEDLSI procedure is used to produce least significant intervals. If two treatments LSIs do not overlap, then these two treatments are significantly different at the specified significant level given in LSD % level field. These LSI limits columns are added to the summary spreadsheet.

Subset entries in summary

When the OK button is selected, the Select Trial Entries dialog will be opened to allow you to choose just a subset of the entries to be in the final report. The analysis still uses the full data set, but the summary tables and graphs are reduced to just show the selected entries.

Include partial years in summary

If this item is ticked, all completed seasons will be summarized, otherwise only seasons belonging to a complete year of results (i.e. all seasons are present in the year) are analysed.

Blocking model in analysis

Automatic analysis	use the VAROWCOLUMNDESIGN procedure to find the optimal spatial model.
Replicates (randomized block)	use analysis of variance with only replicates as the block term.
Replicates + columns	use REML analysis with replicates and columns as the spatial terms.
Replicates/columns	use REML analysis with replicates and columns within replicates as the spatial terms.
Rows + columns	use REML analysis with rows and columns as the spatial terms.
Nearest neighbour (1d – columns)	use REML with an autocorrelation or order 1 along columns as the spatial term.
Nearest neighbour 2d (rows x cols)	use REML analysis with an autocorrelation or order 1 along rows and columns as the spatial terms.

Action buttons

Ok	Run the analysis.
Cancel	Close the window without further changes.