Summary of Trait values in selected Trials
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The least squares mean (LSmean) of a line is the best estimate of that line's mean based on a linear model. If a dataset has missing data, the LSmean adjusts for the expected value of the missing data based on the model, so that the LSmean is less sensitive to missingness than the arithmetic mean.
If two lines have the same true mean value, their estimated mean values are only expected to differ by more than the Least Significant Difference (LSD) in 5% of experiments. If a number of lines have the same true mean value, the maximum difference between any pair of lines is only expected to exceed the Honestly Significant Difference (HSD) in 5% of experiments.
This analysis requires that the selected traits have some measurements in each of the selected trials. When selecting, use the "trials with all traits" option.
Please select at least one trait and one trial, Traits and Trials.The least squares mean (LSmean) of a line is the best estimate of that line's mean based on a linear model. If a dataset has missing data, the LSmean adjusts for the expected value of the missing data based on the model, so that the LSmean is less sensitive to missingness than the arithmetic mean.
If two lines have the same true mean value, their estimated mean values are only expected to differ by more than the Least Significant Difference (LSD) in 5% of experiments. If a number of lines have the same true mean value, the maximum difference between any pair of lines is only expected to exceed the Honestly Significant Difference (HSD) in 5% of experiments.
This analysis requires that the selected traits have some measurements in each of the selected trials. When selecting, use the "trials with all traits" option.