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Companion Package to "Dynamic Prediction in Clinical Survival Analysis"

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CVPL: Calculate cross-validated log-partial likelihood (with...

CVPL: Calculate cross-validated log-partial likelihood (with...
In dynpred: Companion Package to "Dynamic Prediction in Clinical Survival Analysis"

Description Usage Arguments Value Author(s) References Examples

View source: R/CVPL.R

Description

This function calculates the cross-validated log partial likelihood, with shrinkage if requested.

Usage

1
CVPL(formula, data, progress = TRUE, overall = FALSE, shrink = 1)

Arguments

formula

Formula for prediction model to be used as in coxph

data

Data set in which to interpret the formula

progress

if TRUE (default), progress of the cross-validation will be printed

overall

if TRUE, CVPL uses regression coefficient estimates based on the full data, for each observation i, rather than the estimates based on data minus i

shrink

Shrinkage factor; default is 1 (no shrinkage)

Value

Numeric; the cross-validated log partial likelihood

Author(s)

Hein Putter H.Putter@lumc.nl

References

Verweij PJM & van Houwelingen HC (1994), Penalized likelihood in Cox regression, Statistics in Medicine 13, 2427-2436.

van Houwelingen HC, Putter H (2012). Dynamic Prediction in Clinical Survival Analysis. Chapman & Hall.

Examples

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data(ova)
CVPL(Surv(tyears, d) ~ 1, data = ova)
CVPL(Surv(tyears, d) ~ Karn + Broders + FIGO + Ascites + Diam,
  data = ova)
CVPL(Surv(tyears, d) ~ Karn + Broders + FIGO + Ascites + Diam,
  data = ova, overall=TRUE)

Example output

Loading required package: survival
1/3582/3583/3584/3585/3586/3587/3588/3589/35810/35811/35812/35813/35814/35815/35816/35817/35818/35819/35820/35821/35822/35823/35824/35825/35826/35827/35828/35829/35830/35831/35832/35833/35834/35835/35836/35837/35838/35839/35840/35841/35842/35843/35844/35845/35846/35847/35848/35849/35850/35851/35852/35853/35854/35855/35856/35857/35858/35859/35860/35861/35862/35863/35864/35865/35866/35867/35868/35869/35870/35871/35872/35873/35874/35875/35876/35877/35878/35879/35880/35881/35882/35883/35884/35885/35886/35887/35888/35889/35890/35891/35892/35893/35894/35895/35896/35897/35898/35899/358100/358101/358102/358103/358104/358105/358106/358107/358108/358109/358110/358111/358112/358113/358114/358115/358116/358117/358118/358119/358120/358121/358122/358123/358124/358125/358126/358127/358128/358129/358130/358131/358132/358133/358134/358135/358136/358137/358138/358139/358140/358141/358142/358143/358144/358145/358146/358147/358148/358149/358150/358151/358152/358153/358154/358155/358156/358157/358158/358159/358160/358161/358162/358163/358164/358165/358166/358167/358168/358169/358170/358171/358172/358173/358174/358175/358176/358177/358178/358179/358180/358181/358182/358183/358184/358185/358186/358187/358188/358189/358190/358191/358192/358193/358194/358195/358196/358197/358198/358199/358200/358201/358202/358203/358204/358205/358206/358207/358208/358209/358210/358211/358212/358213/358214/358215/358216/358217/358218/358219/358220/358221/358222/358223/358224/358225/358226/358227/358228/358229/358230/358231/358232/358233/358234/358235/358236/358237/358238/358239/358240/358241/358242/358243/358244/358245/358246/358247/358248/358249/358250/358251/358252/358253/358254/358255/358256/358257/358258/358259/358260/358261/358262/358263/358264/358265/358266/358267/358268/358269/358270/358271/358272/358273/358274/358275/358276/358277/358278/358279/358280/358281/358282/358283/358284/358285/358286/358287/358288/358289/358290/358291/358292/358293/358294/358295/358296/358297/358298/358299/358300/358301/358302/358303/358304/358305/358306/358307/358308/358309/358310/358311/358312/358313/358314/358315/358316/358317/358318/358319/358320/358321/358322/358323/358324/358325/358326/358327/358328/358329/358330/358331/358332/358333/358334/358335/358336/358337/358338/358339/358340/358341/358342/358343/358344/358345/358346/358347/358348/358349/358350/358351/358352/358353/358354/358355/358356/358357/358358/358[1] NA
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dynpred documentation built on May 2, 2019, 5:07 a.m.

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