Plots least significant intervals, saved from
SEDLSI (M.C. Hannah).
||Window in which to plot the graph|
||Title for the graph; default
||Title for the y-axis; default
||Defines the least significant intervals|
||Symbol to use to plot each set of estimates|
||Colour for each symbol|
||Multiplier to use in the calculation of the size of each symbol|
||Multiplier to use in the calculation of the size of the labels in each plot|
Least significant intervals (LSIs) are used for comparing a set of estimates (e.g. predicted means from
ANOVA or regression) graphically, especially when their SEDs differ. LSIs are intervals (or error bars) that are designed to overlap where there is no significant difference between estimates, and to be disjoint (i.e. not to overlap) where there are significant differences.
LSIs can be calculated by the
SEDLSI procedure and saved, in a pointer, using its
LSI parameter. This pointer can then be be supplied as input to
LSIPLOT, using its own
LSI parameter, to plot the intervals on a later occasion.
LSIPLOT has an option
WINDOW to specify the window in which to plot the LSIs. By default a window is defined internally, within
LSIPLOT, to fill the whole screen. The
TITLE option allows you to supply a title for the plot (default
'Estimates with LSIs by Treatment'), and the
YTITLE option supplies a title for the y-axis (default
SYMBOL parameter specifies the symbol to use to plot the estimates; by default, this is a circle. The
CSYMBOL parameter specifies the colour (default black). The
SMLABEL parameters specify the multipliers to use when calculating the sizes of the symbols and the labels, instead of the default values calculated by the procedure.
Commands for: Graphics.
CAPTION 'LSIPLOT example',\ !t('Experiment on foster feeding of rats from Scheffe (1959)',\ 'The Analysis of Variance; also see McConway, Jones & Taylor (1999)',\ 'Statistical Modelling using GENSTAT, Example 7.6.'); STYLE=meta,plain FACTOR [NVALUES=61; LABELS=!t('A','B','I','J')] litter READ litter; FREPRESENTATION=labels A A A A A A A A A A A A A A A A A B B B B B B B B B B B B B B B I I I I I I I I I I I I I I J J J J J J J J J J J J J J J : FACTOR [NVALUES=61; LABELS=!t('A','B','I','J')] mother READ mother; FREPRESENTATION=labels A A A A A B B B I I I I J J J J J A A A A B B B B B I I I I J J A A A B B B I I I I I J J J A A A A B B B I I I J J J J J : VARIATE [NVALUES=61] littwt READ littwt 61.5 68.2 64 65 59.7 55 42 60.2 52.5 61.8 49.5 52.7 42 54 61 48.2 39.6 60.3 51.7 49.3 48 50.8 64.7 61.7 64 62 56.5 59 47.2 53 51.3 40.5 37 36.3 68 56.3 69.8 67 39.7 46 61.3 55.3 55.7 50 43.8 54.5 59 57.4 54 47 59.5 52.8 56 45.2 57 61.4 44.8 51.5 53 42 54 : MODEL littwt FIT [PRINT=accumulated; FPROBABILITY=yes] litter*mother RKEEP DF=rdf PREDICT [PREDICTIONS=mean; VCOVARIANCE=var] mother SEDLSI [PLOT=*; DF=rdf] mean; VCOVARIANCE=var; LSI=lsi LSIPLOT [TITLE='Means and least significant intervals'; YTITLE='Weight'] lsi