Genstat has a comprehensive set of facilities for design of experiments. Collectively, these are known as the Genstat Design System. Many different design types are covered, each with a procedure that allows you to view and choose from the available possibilities. Other procedure allow designs and data forms to be displayed. There is also a general procedure DESIGN
that can be used interactively to provide a single point of access to all the design types. DESIGN
and the AG
… procedures that it calls provide the Select Design facilities in Genstat for Windows, while the alternative Standard Design menu uses AGHIERARCHICAL
, AGLATIN
and AGSQLATTICE
to generate completely randomized designs, randomized blocks, Latin and GraecoLatin squares, splitplots, stripplots (or crisscross designs) and lattices.
DESIGN 
provides a menudriven interface for selecting and generating experimental designs 

AGALPHA 
forms alpha designs for up to 100 treatments 
AGBIB 
generates balancedincompleteblock designs 
AGBOXBEHNKEN 
generates BoxBehnken designs 
AGCENTRALCOMPOSITE 
generates central composite designs 
AGCROSSOVERLATIN 
generates Latin squares balanced for carryover effects 
AGCYCLIC 
generates cyclic designs from standard generators 
AGDESIGN 
generates generally balanced designs – factorial designs with blocking, fractional factorial designs, Lattice squares etc. 
AGFACTORIAL 
generates minimum aberration complete and fractional factorial designs 
AGFRACTION 
generates fractional factorial designs 
AGHIERARCHICAL 
generates orthogonal hierarchical designs 
AGINDUSTRIAL 

AGLATIN 
generates mutually orthogonal Latin squares 
AGLOOP 
generates loop designs e.g. for timecourse microarray experiments 
AGMAINEFFECT 
generates designs to estimate main effects of twolevel factors 
AGNEIGHBOUR 
generates neighbourbalanced designs 
AGNONORTHOGONALDESIGN 
generates nonorthogonal multistratum designs 
AGSPACEFILLINGDESIGN 
generates space filling designs 
AGQLATIN 
generates complete and quasicomplete Latin squares 
AGREFERENCE 
generates referencelevel designs e.g. for microarray experiments 
AGSEMILATIN 
generates semiLatin squares 
AGSQLATTICE 
generates square lattice and lattice square designs 
PDESIGN 
prints treatment combinations tabulated by the block factors 
DDESIGN 
plots the plan of a design 
ADSPREADSHEET 
puts the data and plan of an experimental design into Genstat spreadsheets 
There are also procedures that you can use to determine the sample size (i.e. replication) required for experiments that are to be analysed by analysis of variance, ttest or various nonparametric tests. You can also calculate the power (or probability of detection) for terms in analysis of variance or regression analyses.
APOWER 
calculates the power (probability of detection) for terms in an analysis of variance 

RPOWER 
calculates the power (probability of detection) for regression models 
VPOWER 
uses a parametric bootstrap to estimate the power (probability of detection) for terms in a REML analysis 
ASAMPLESIZE 
finds the replication (sample size) to detect a treatment effect or contrast 
VSAMPLESIZE 
estimates the replication to detect a fixed term or contrast in a REML analysis, using parametric bootstrap 
ADETECTION 
calculates the minimum size of effect or contrast detectable in an analysis of variance 
SBNTEST 
calculates the sample size for binomial tests 
SCORRELATION 
calculates the sample size to detect specified correlations 
SLCONCORDANCE 
calculates the sample size for Lin’s concordance coefficient 
SMANNWHITNEY 
calculates the sample size for the MannWhitney test 
SMCNEMAR 
calculates the sample size for McNemar’s test 
SPNTEST 
calculates the sample size for a Poisson test 
SPRECISION 
calculates the sample size to obtain a specified precision 
SSIGNTEST 
calculates the sample size for a sign test 
STTEST 
calculates the sample size for ttests, including equivalence tests and tests for noninferiority 
DSTTEST 
plots power and significance for ttests, including equivalence tests and tests for noninferiority 
The Design System is based on a range of standard generators. Some of these, such as the Galois fields used to generate Latin squares, can be formed when required – and so there is no limitation on the available designs. Repertoires of others, such as design keys, are stored in backingstore files which are scanned by the design generation procedures to form menus listing the available possibilities. Algorithms are available to form generators for new designs, and these can then be added to the design files to become an integral part of the system. Other design utilities include procedures for combining simple designs into more complicated arrangements, for forming augmented designs, and for determining how many replicates are needed. There is also a directive for constructing responsesurface designs. The relevant commands include the directives…
AFMINABERRATION 
forms minimum aberration factorial or fractionalfactorial designs 

AFRESPONSESURFACE 
uses the BLKL algorithm to construct designs for estimating response surfaces 
GENERATE 
generates values of factors in systematic order or as defined by a design key, or forms values of pseudofactors 
RANDOMIZE 
puts units of vectors into random order, or randomizes units of an experimental design 
FKEY 
forms design keys for multistratum experimental designs, allowing for confounding and aliasing of treatments 
FPSEUDOFACTORS 
determines patterns of confounding and aliasing from design keys, and extends the treatment formula to incorporate the necessary pseudofactors 
SET2FORMULA 
forms a model formula using structures supplied in a pointer 
and the procedures.
AEFFICIENCY 
calculates efficiency factors for experimental designs 

AFAUGMENTED 
forms an augmented design 
AFLABELS 
forms a variate of unit labels for a design 
AFUNITS 
forms a factor to index the units of the final stratum of a design 
AKEY 
generates values for treatment factors using the design key method 
AMERGE 
merges extra units into an experimental design 
AFNONLINEAR 
forms Doptimal designs to estimate the parameters of a nonlinear or generalized linear model 
AFPREP 
searches for an efficient partiallyreplicated design 
APRODUCT 
forms a new experimental design from the product of two designs 
ARANDOMIZE 
randomizes and prints an experimental design 
COVDESIGN 
produces experimental designs efficient under analysis of covariance 
FACCOMBINATIONS 
forms a factor to indicate observations with identical combinations of values of a set of variates, texts or factors 
FACDIVIDE 
represents a factor by factorial combinations of a set of factors 
FACPRODUCT 
forms a factor with a level for every combination of other factors 
FBASICCONTRASTS 
forms the basic contrasts of a model term 
FCOMPLEMENT 
forms the complement of an incomplete block design 
FDESIGNFILE 
forms a backingstore file of information for AGDESIGN 
FHADAMARDMATRIX 
forms Hadamard matrices 
FOCCURRENCES 
forms a “concurrence” matrix recording how often each pair of treatments occurs in the same block of a design 
FPROJECTIONMATRIX 
forms a projection matrix for a set of model terms 
XOEFFICIENCY 
calculates the efficiency for estimating effects in crossover designs 
XOPOWER 
estimates the power of contrasts in crossover designs 