SAP HANA Predictive Analysis Library (PAL)

UPDATE PAL_DISTRPROB_DISTRPARAM_TBL SET VALUEE = (SELECT VAL FROM
PAL_DISTRFIT_ESTIMATION_TBL WHERE NAME = 'MEAN') WHERE NAME = 'MEAN';
UPDATE PAL_DISTRPROB_DISTRPARAM_TBL SET VALUEE = (SELECT VAL*VAL FROM
PAL_DISTRFIT_ESTIMATION_TBL WHERE NAME = 'SD') WHERE NAME = 'VARIANCE';
SELECT * FROM PAL_DISTRPROB_DISTRPARAM_TBL;
DROP TABLE #PAL_CONTROL_TBL;
CREATE LOCAL TEMPORARY COLUMN TABLE #PAL_CONTROL_TBL(NAME VARCHAR (50),INTARGS
INTEGER,DOUBLEARGS DOUBLE,STRINGARGS VARCHAR (100));
INSERT INTO #PAL_CONTROL_TBL VALUES ('LOWER_UPPER',0,null,null);
DROP TABLE PAL_DISTRPROB_RESULT_TBL;
CREATE TABLE PAL_DISTRPROB_RESULT_TBL LIKE PAL_DISTRPROB_RESULT_T;
CALL DM_PAL.PAL_DISTRPROB_PROC(PAL_DISTRPROB_DATA_TBL,
PAL_DISTRPROB_DISTRPARAM_TBL, #PAL_CONTROL_TBL, PAL_DISTRPROB_RESULT_TBL) WITH
OVERVIEW;
SELECT * FROM PAL_DISTRPROB_RESULT_TBL;
The expected result is as follows:
4.3 Scenario: Survival Analysis
In clinical trials or community trials, the effect of an intervention is assessed by measuring the number of
subjects who have survived or are saved after that intervention over a period of time. We wish to measure the
survival probability of Dukes’C colorectal cancer patients after treatment and evaluate statistically whether
the patients who accept treatment can survive longer than those who are only controlled conservatively.
Option 1: Kaplan-Meier Estimate
Technology Background
Kaplan-Meier estimate is one of the simplest way to measure the fraction of subjects living for a certain
amount of time after treatment. The time starting from a defined point to the occurrence of a given event, for
example death, is called as survival time.
This scenarios describes a clinical trial of 49 patients for the treatment of Dukes’C colorectal cancer. The
following data shows the survival time in 49 patients with Dukes’C colorectal cancer who are randomly
assigned to either linoleic acid or control treatment.
Table 429:
Treatment
Survival Time (months)
Linoleic acid (n = 25) 1+, 5+, 6, 6, 9+, 10, 10, 10+, 12, 12, 12, 12, 12+, 13+, 15+, 16+,
20+, 24, 24+, 27+, 32, 34+, 36+, 36+, 44+
SAP HANA Predictive Analysis Library (PAL)
End-to-End Scenarios P U B L I C 565