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  2. A2RESULTSUMMARY procedure


Provides a summary of results from an analysis by A2WAY(R.W. Payne).


PRINT = string tokens What to print (description, means, significant); default desc, mean, sign
PSE = string tokens Standard errors to be printed with the means (sed, sedsummary, lsd, lsdsummary, dfmeans); default sed, dfme
LSDLEVEL = scalar Significance level (%) for least significant differences; default 5
SAVE = pointer Save structure from A2WAY; default uses the save structure from the most recentA2WAYanalysis

No parameters


A2RESULTSUMMARY investigates an A2WAY analysis, to provide the information that would be useful for a report. By default, all the information is printed, but you can control this with the PRINT option, whose settings are:

description prints the name of the y-variate, any covariates and the block and treatment models,
means prints relevant tables of means, and
significant lists the significant treatment terms.

The relevant tables of means are those that contain significant treatment effects. If the interaction is significant in an analysis with two treatment factors, the relevant table is just the two-way table of means. Otherwise the relevant tables consist of the one-way tables of means for any significant main effect.

The PSE option controls the information provided with the tables of means:

sed standard errors for differences between means,
sedsummary summary of the standard errors for differences,
dfmeans degrees of freedom for the standard errors of differences,
lsd least significant differences between the means, and
lsdsummary summary of the least significant differences.

The default is to print the standard errors of differences and their degrees of freedom.

The LSDLEVEL option specifies the significance level (%) to use in the calculation of least significant differences (default 5%).

Parameters: none.

See also

Commands for: Analysis of variance.


          !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.')
FACTOR  [NVALUES=61; LABELS=!t(A,B,I,J)] Litter,Mother
READ    Litter,Mother,Littwt; FREPRESENTATION=labels
A A 61.5  A A 68.2  A A 64.0  A A 65.0  A A 59.7  A B 55.0  A B 42.0
A B 60.2  A I 52.5  A I 61.8  A I 49.5  A I 52.7  A J 42.0  A J 54.0
A J 61.0  A J 48.2  A J 39.6  B A 60.3  B A 51.7  B A 49.3  B A 48.0
B B 50.8  B B 64.7  B B 61.7  B B 64.0  B B 62.0  B I 56.5  B I 59.0
B I 47.2  B I 53.0  B J 51.3  B J 40.5  I A 37.0  I A 36.3  I A 68.0
I B 56.3  I B 69.8  I B 67.0  I I 39.7  I I 46.0  I I 61.3  I I 55.3
I I 55.7  I J 50.0  I J 43.8  I J 54.5  J A 59.0  J A 57.4  J A 54.0
J A 47.0  J B 59.5  J B 52.8  J B 56.0  J I 45.2  J I 57.0  J I 61.4
J J 44.8  J J 51.5  J J 53.0  J J 42.0  J J 54.0 :
A2WAY     [PRINT=*; PLOT=*; TREATMENTS=Litter,Mother] Littwt
A2DISPLAY [PRINT=aovtable,means]
A2RESULTSUMMARY [PSE=lsd,lsdsummary]
Updated on September 11, 2019

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