| 9.1 |
The GLMPOWER procedure
|
determining the sample
characterizing the power of a study to detect a meaningful effect
conducting what-if analyses to assess sensitivity of the power or required sample size to other factors
You specify the design and the
| 9.1 |
The new
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The new SURVIVAL statement enables you to create confidence bands (also known as simultaneous confidence intervals) for the
The OUT= option
The CONFTYPE= option specifies the transformation applied to
S
(
t
) to obtain the pointwise confidence intervals and the confidence bands. Four transforms are available: the arcsine-square root transform, the complementary log-log transform, the
The CONFBAND= option specifies the confidence bands to add to the OUT= data set. You can choose the equal precision confidence bands (Nair 1984), or the Hall-Wellner bands (Hall and Wellner 1980), or both.
The BANDMAX= option specifies the maximum time for the confidence bands.
The BANDMIN= option specifies the minimum time for the confidence bands.
The STDERR option adds the column of standard error of the estimated survivor function to the OUT= data set.
The ALPHA= option sets the confidence level for pointwise confidence intervals as well as the confidence bands.
| 9.1 |
The LIFETEST procedure now provides additional tests for comparing two or more samples of survival data, including the Tarone-Ware test, Peto-Peto test, modified Peto-Peto test, and the Fleming-Harrington
G
family of tests. Trend tests for ordered alternatives can be
|
| 9.1 |
The LOESS procedure now
|
The new SCORE statement enables you to score new data sets and compute fit statistics and ROC curves without refitting the model. Information for a fitted model can be saved to a SAS data set with the OUTMODEL= option, while the INMODEL= option inputs the model information required for the scoring.
The new STRATA statement enables you to perform conditional logistic regression on highly stratified data using the method of Gail, Lubin, and Rubenstein (1981). The OFFSET option is now enabled for logistic regression.
The LOGISTIC procedure now forms classification groups using the full formatted length of the CLASS variable levels.
Several new CLASS parameterizations are available: ordinal, orthogonal effect, orthogonal reference, and orthogonal ordinal.
You can now output the design matrix using the new OUTDESIGN= option.
The definition of concordance has been changed to make it more meaningful for ordinal models. The new definition is consistent with that used in previous releases for the binary response model.
| 9.1 |
Enhancements for the exact
|
For an exact conditional analysis, specifying the STRATA statement