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AMTKEEP procedure

Saves information from the analysis of a multitiered design by AMTIER (C.J. Brien & R.W. Payne).


RESIDUALS = variate Saves the residuals
FITTEDVALUES = variate Saves the fitted values
AOVTABLE = pointer Saves the analysis-of-variance table
SKELETON = string token Whether to save only the skeleton analysis-of-variance table (yes, no); default no
PSEUDOLINES = string token Whether to include lines for pseudo-terms in the analysis-of-variance table (yes, no); default no
OMITMISSINGLINES = string token Whether to omit lines of the analysis-of-variance table that contain only missing values (yes, no); default no
SAVE = pointer Save structure for the analysis; if this is not set, information is saved from the most recent AMTIER analysis

No parameters


The AMTIER procedure analyses data from designs that require up to three model formulae to specify their analysis (resulting from three or more tiers for the experiment). Information from an AMTIER analysis can be saved by the SAVE parameter, and input to AMTKEEP using its own SAVE parameter. Alternatively, if SAVE is not set, AMTKEEP will use the information from the most recent AMTIER analysis.

The RESIDUALS and FITTEDVALUES options save the residuals and fitted values, respectively, in variates.

The AOVTABLE option saves the analysis-of-variance table. You can set option PSEUDOLINES=yes to include lines for all the component pseudo-terms of a term; by default lines are included only for the term itself. You can set option SKELETON=yes to obtain a “skeleton” analysis of variance, omitting the columns for sums of squares, mean squares and variance ratios. You can set option OMITMISSINGLINES=yes to omit lines of the analysis-of-variance table, such as stratum headers, that contain only missing values.


Parameters: none.


Multitiered experiments are defined by Brien (1983), their design is discussed by Brien & Bailey (2006) and Brien et al. (2011), and their analysis of variance is described by Brien & Payne (1999), Brien & Bailey (2009) and Bailey & Brien (2013).


Bailey, R.A. & Brien C.J. (2013). Randomization-based models for multitiered experiments. I. A chain of randomizations. arXiv preprint arXiv:1310.4132: 30.

Brien, C.J. (1983). Analysis of variance tables based on experimental structure. Biometrics, 39, 53-59.

Brien, C.J. & Bailey, R.A. (2006). Multiple randomizations. Journal of the Royal Statistical Society, Series B, 68, 571-609.

Brien, C.J. & Bailey, R.A. (2009). Decomposition tables for multitiered experiments. I. A chain of randomizations. The Annals of Statistics, 36, 4184-4213.

Brien, C.J., Harch, B.D., Correll, R.L. & Bailey, R.A. (2011). Multiphase experiments with at least one later laboratory phase. I. Orthogonal designs. Journal of Agricultural, Biological and Environmental Statistics, 16, 422-450.

Brien, C.J. & Payne, R.W. (1999). Tiers, structure formulae and the analysis of complicated experiments. The Statistician, 48, 41-52.

See also


Commands for: Analysis of variance.


CAPTION 'AMTKEEP example','Example from Brien & Payne (1999).';\
SPLOAD  [PRINT=*] '%gendir%/examples/Amtier.gsh'
        F2=(Rows*(Squares/Columns))/Halfplots; F3=Trellis*Method] Score
PRINT   aovtable[]
Updated on March 11, 2019

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