Forms predictions from an unbalanced analysis of variance, performed by AUNBALANCED
(R.W. Payne).
Options
PRINT = string tokens |
What to print (description , predictions , se , sed , sedsummary , ese , lsd , lsdsummary , vcovariance ); default pred , sed |
---|---|
MODEL = formula |
Model to use to calculate the predictions; default * i.e. full model fitted by AUNBALANCED |
FACTORIAL = scalar |
Limit on number of factors or variates in each term specified by MODEL ; default 3 |
COMBINATIONS = string token |
Factor combinations for which to form predicted means (present , estimable ); default esti |
ADJUSTMENT = string token |
Type of adjustment to be made when predicting means (marginal , equal , observed ); default marg |
WEIGHTS = table |
Weights classified by some or all of the factors in the model |
PREDICTIONS = tables or scalars |
Saves predictions; default * |
SE = tables or scalars |
Saves standard errors of predictions; default * |
SED = symmetric matrices |
Saves matrices of standard errors of differences between predictions; default * |
ESE = table |
Saves effective standard errors; default * |
LSD = symmetric matrix |
Saves least significant differences between predictions; default * |
LSDLEVEL = scalar |
Significance level (%) for least significant differences; default 5 |
VCOVARIANCE = symmetric matrices |
Saves variance-covariance matrices of predictions; default * |
SAVE = identifier |
Save structure (from AUNBALANCED ) containing details of the analysis for which predictions are required; if omitted, output is from the most recent use of AUNBALANCED |
Parameters
CLASSIFY = vectors |
Variates and/or factors to classify table of predictions |
---|---|
LEVELS = variates or scalars |
To specify values of variates, levels of factors |
Description
AUPREDICT
can produce predicted means following an analysis of variance of an unbalanced design by AUNBALANCED
. The predictions are calculated using the PREDICT
directive. The first step (A) of the calculation forms a full table of predictions, classified by every factor in the model. The second step (B) averages the full table over the factors that do not occur in the table of means.
The COMBINATIONS
option specifies which cells of the full table are to be formed in Step A. The default setting, estimable
, fills in all the cells other than those that involve parameters that cannot be estimated, for example because of aliasing. Alternatively, setting COMBINATIONS=present
excludes the cells for factor combinations that do not occur in the data. The ADJUSTMENT
and WEIGHTS
options then define how the averaging is done in Step B. The WEIGHTS
option allows you to specify your own table of weights to use in the averaging. Alternatively, if WEIGHTS
is not set, the weights are formed automatically according to the setting of the ADJUSTMENT
option. The default setting, marginal
, of ADJUSTMENT
forms a table of marginal weights for each factor, containing the proportion of observations with each of its levels; the full table of weights is then formed from the product of the marginal tables. The setting equal
weights all the combinations equally. Finally, the setting observed
uses the WEIGHTS
option of PREDICT
to weight each factor combination according to its own individual replication in the data.
Printed output, which extends the output available from PREDICT
, is controlled by settings of the PRINT
option:
description |
standardization policies used when forming the predictions, |
---|---|
predictions |
predictions, |
se |
predictions and standard errors, |
sed |
standard errors for differences between the predictions, |
sedsummary |
summary of the standard errors for differences between the predictions, |
lsd |
least significant differences between the predictions, |
lsdsummary |
summary of the least significant differences between the predictions, |
ese |
approximate effective standard errors – these are formed by procedure SED2ESE with the aim of allowing good approximations to the standard errors for differences to be calculated by the usual formula of sedi,j = √( esei2 + esej2 ), and |
vcovariance |
variance and covariances of the predictions. |
The default is to print predictions and a summary of the standard errors of differences. The standard errors (and sed’s) are relevant for the predictions when considered as means of those data that have been analysed, with the means formed according to the averaging policy defined by the options of PREDICT
. The word prediction is used because these are predictions of what the means would have been if the factor levels been replicated differently in the data; see Lane & Nelder (1982) for more details. The LSDLEVEL
option specifies the significance level (%) to use in the calculation of least significant differences (default 5%).
Another extension in AUPREDICT
is that you can produce predictions using a smaller model than the full model that has been fitted by AUNBALANCED
. This can be useful if the full model contains many parameters. A substantial amount of time and computer workspace may then be needed to calculate the predictions and standard errors. Very large models may even exceed the capacity of some PCs.
You might choose to omit a term from the full model when forming a particular table of predictions if the term is orthogonal to all the terms involved in the table. For example, you might omit the term blocks
when forming an A
-by-B
table of predictions if each combination of levels of the factors A
and B
is replicated the same number of times in every block. The justification is that an orthogonal term cannot affect the size of any of the differences between predictions. Different weighting of the levels of the orthogonal term may affect the overall mean of the predictions, but this is usually unimportant. If you omit the term, it is though you had included it with weightings based on the observed replication of its levels in the data set – and in any well-designed data set these should provide a satisfactory outcome. You might also omit a term if it is nearly orthogonal to the terms involved in the table, and you are happy to ignore its effect on the predictions.
The model is specified by the MODEL
option. The FACTORIAL
option sets a limit on number of factors or variates in each term specified by MODEL
; default 3.
The PREDICTIONS
, SE
, SED
, ESE
, LSD
and VCOVARIANCE
options allow the results of the prediction to be save in appropriate Genstat data structures.
The SAVE
option allows you to specify save structure from the analysis for which further output is required. If SAVE
is not set, output will be produced for the most recent analysis from AUNBALANCED
; however, none of the Genstat regression directives (MODEL
, TERMS
, FIT
, ADD
, DROP
and so on) must then have been used in the interim.
Options: PRINT
, MODEL
, FACTORIAL
, COMBINATIONS
, ADJUSTMENT
, WEIGHTS
, PREDICTIONS
, SE
, SED
, ESE
, LSD
, LSDLEVEL
, VCOVARIANCE
, SAVE
.
Parameters: CLASSIFY
, LEVELS
.
Method
The predictions are produced using the PREDICT
directive.
Reference
Lane, P.W. & Nelder, J.A. (1982). Analysis of covariance and standardization as instances of prediction. Biometrics, 38, 613-621.
See also
Directive: PREDICT
.
Procedures: AUNBALANCED
, AUDISPLAY
, AUGRAPH
, AUMCOMPARISON
, AUKEEP
.
Commands for: Analysis of variance.
Example
CAPTION 'AUPREDICT example',\ 'Data from Genstat 5 Release 1 Reference Manual, page 340.';\ STYLE=meta,plain FACTOR [NVALUES=36; LEVELS=3; VALUES=12(1...3)] Block FACTOR [NVALUES=36; LABELS=!t(baresoil,emerald,emergo)] Leachate & [LABELS=!t('1','1/4','1/16','1/64')] Dilution VARIATE [NVALUES=36] Nhatch,Nnohatch READ Leachate,Dilution,Nhatch,Nnohatch 1 2 109 318 3 4 54 350 3 1 * 415 2 2 783 212 3 3 652 1375 2 4 490 816 1 3 95 1219 2 1 1012 66 1 4 166 943 3 2 1059 313 1 1 257 1006 2 3 1058 234 2 4 507 1119 1 2 194 840 1 3 175 1707 1 1 326 609 3 4 142 980 2 3 286 230 3 2 546 313 2 2 * 301 2 1 2471 112 3 3 76 489 1 4 208 503 3 1 * 325 1 1 322 913 1 2 255 2246 3 2 1774 1446 2 2 999 193 2 4 388 1836 3 4 221 1800 1 3 220 1902 2 1 2821 187 3 1 1486 463 3 3 717 1473 1 4 143 941 2 3 968 550 : CALCULATE Logit%h = LOG(Nhatch/Nnohatch) BLOCKSTRUCTURE Block TREATMENTSTRUCTURE Leachate*Dilution AUNBALANCED [PRINT=aovtable] Logit%h AUPREDICT Leachate & Dilution & Leachate,Dilution