LSIPLOT procedure

Plots least significant intervals, saved from SEDLSI (M.C. Hannah).

Options

Parameter

Description

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 'Estimates').

Options: WINDOW, TITLE, YTITLE.

Parameter: LSI.

See also

Procedures: SEDLSI, SED2ESE.

Commands for: Graphics.

Example

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