SURVIVAL.COX.CV OpenBI

A penalized Cox model's cross-validation: the deviance at each penalty, and the one chosen.

Group: Survival analysis. OpenBI’s own: DAX has no function of this name.

Syntax

SURVIVAL.COX.CV ( <table>, <duration>, <event> [, <options>] [, <entry>], <name>, <covariate> [, <name>, <covariate>] … )

Parameter	Type	Description
`table`	Table	The rows to follow, one a subject such as a customer, a policy or a machine: a table of the model or a table expression, as the filters leave it.
`duration`	Number evaluated for each row	How long each row was followed: until its event, or until we stopped seeing it. In any unit (days, months, years), the same for every row.
`event`	Number evaluated for each row	1 or TRUE when the row's duration ended in the event (the customer left); 0 or FALSE when it did not, so all we know is that it lasted at least that long (censored).
`options`	Text optional	Settings in one text, name=value with commas between: alpha (1 when left out), folds (10), seed (1), nlambda (100) and ratio.
`entry`	Number optional, evaluated for each row	When each row came under observation: it is at risk from just after its entry to the end of its duration. An expression, not a text, given right before the first name.
`name`	Text repeatable	A covariate's name, in quotes: the result calls it so.
`covariate`	Expression repeatable, evaluated for each row	The covariate's value on each row: a number, or a text for a factor whose levels are each compared with the first.

Returns

Table. A row a lambda, the largest first. The columns: Lambda and Log lambda; Deviance, its Std error, Lower and Upper; Nonzero; Deviance ratio; and Chosen.

Remarks

The fit is the elastic net for Cox's model, as R's glmnet computes it (Efron's handling of ties): alpha=1 is the lasso, which can drop terms altogether; alpha=0 is ridge, which only shrinks them.
The terms are put on a common scale before the penalty, as glmnet does, and the coefficients come back on the covariates' own scale.
The path runs over nlambda values of lambda (100 by default, from 5 to 500), from the smallest that keeps every term at 0 down to ratio times it (0.0001, or 0.01 when there are fewer rows than terms).
Lambda is chosen by cross-validation: the rows are split into folds (10 by default, from 3 to 50; at least twice as many rows as folds), shuffled with the seed (1 by default; seed=0 keeps the rows' order), and each fold is scored by its deviance. Another seed can choose another lambda.
Deviance is the cross-validated deviance per row at that lambda (lower is better), Lower and Upper one standard error either side: the curve to choose lambda on.
Nonzero counts the terms still in the model. Deviance ratio is the share of the deviance the fit on all the rows explains.
Chosen marks the lambda with the least deviance (min) and the largest within one standard error of it (1se), the two SURVIVAL.COX.PENALIZED can take.

Compared with DAX

An OpenBI function: DAX has none like it, so a measure or query that uses it works in OpenBI only, not in Power BI or Analysis Services.

Examples

Ten lambdas, four folds

EVALUATE
VAR Customers =
    DATATABLE (
        "Plan", STRING, "Months", INTEGER, "Left", INTEGER, "Spend", INTEGER, "Tickets", INTEGER,
        {
            { "Basic", 3, 1, 20, 4 }, { "Basic", 5, 1, 25, 3 }, { "Basic", 6, 0, 40, 1 }, { "Basic", 8, 1, 30, 5 },
            { "Plus", 9, 1, 35, 2 }, { "Basic", 10, 0, 45, 0 }, { "Basic", 12, 1, 28, 3 }, { "Plus", 14, 0, 60, 1 },
            { "Plus", 15, 1, 38, 4 }, { "Basic", 16, 0, 50, 1 }, { "Plus", 18, 1, 42, 2 }, { "Plus", 20, 0, 55, 0 },
            { "Basic", 22, 1, 33, 2 }, { "Plus", 24, 0, 65, 1 }, { "Plus", 25, 1, 48, 3 }, { "Basic", 27, 0, 36, 0 },
            { "Plus", 30, 1, 52, 1 }, { "Plus", 32, 0, 70, 0 }, { "Basic", 34, 0, 44, 2 }, { "Plus", 36, 0, 58, 1 },
            { "Basic", 4, 1, 22, 2 }, { "Plus", 7, 1, 30, 3 }, { "Basic", 13, 1, 26, 1 }, { "Plus", 28, 0, 62, 2 }
        }
    )
RETURN
    SELECTCOLUMNS (
        SURVIVAL.COX.CV ( Customers, [Months], [Left], "folds=4, nlambda=10", "Plan", [Plan], "Spend", [Spend], "Tickets", [Tickets] ),
        "Lambda", [Lambda],
        "Nonzero", [Nonzero],
        "Deviance", [Deviance],
        "Lower", [Lower],
        "Upper", [Upper],
        "Chosen", [Chosen]
    )

Lambda	Nonzero	Deviance	Lower	Upper	Chosen
0.587607236285896	0	3.69980580459434	3.29805292735439	4.10155868183428	(blank)
0.211175091471473	2	2.77097359456228	2.5083988117379	3.03354837738666	(blank)
0.0758923929185371	3	2.27696812724918	2.11191372845161	2.44202252604675	(blank)
0.0272743118649468	3	1.85203863051635	1.65755346589623	2.04652379513647	1se
0.00980187946511145	3	1.83747058120452	1.64239450632105	2.03254665608799	min
0.00352261283526835	3	2.11840951075657	1.76524565133098	2.47157337018215	(blank)
0.0012659614139681	3	3.00436369919286	1.83894181354295	4.16978558484277	(blank)
0.000454962942736797	3	4.88043283981263	1.86778478316533	7.89308089645993	(blank)
0.000163505204013226	3	6.97484052524515	1.8783452285005	12.0713358219898	(blank)
5.87607236285896e-05	3	9.16808782599264	1.88271840466881	16.4534572473165	(blank)

SURVIVAL.COX.PENALIZED, SURVIVAL.COX.PATH, SURVIVAL.COX.

Last updated 3 November 2026 · OpenBI Studio 0.3.74