Prostate Cancer Data — Prostate • islasso

This dataset originates from a study examining the correlation between prostate-specific antigen levels and various clinical measures in men scheduled for radical prostatectomy. It contains 97 rows and 9 variables.

Format

A data frame with 97 observations and 9 variables:

lcavol: Log of cancer volume
lweight: Log of prostate weight
age: Age of the patient
lbph: Log of benign prostatic hyperplasia amount
svi: Seminal vesicle invasion (binary)
lcp: Log of capsular penetration
gleason: Gleason score
pgg45: Percentage of Gleason scores 4 or 5
lpsa: Log of prostate-specific antigen

Source

Stamey, T.A., et al. (1989). Prostate specific antigen in the diagnosis and treatment of adenocarcinoma of the prostate: II. radical prostatectomy treated patients. Journal of Urology, 141(5), 1076-1083.

References

Stamey, T.A., Kabalin, J.N., McNeal, J.E., Johnstone, I.M., Freiha, F., Redwine, E.A., and Yang, N. (1989). Journal of Urology, 141(5), 1076-1083.

Examples

data(Prostate)
summary(Prostate)
#>      lcavol           lweight           age             lbph        
#>  Min.   :-1.3471   Min.   :2.375   Min.   :41.00   Min.   :-1.3863  
#>  1st Qu.: 0.5128   1st Qu.:3.376   1st Qu.:60.00   1st Qu.:-1.3863  
#>  Median : 1.4469   Median :3.623   Median :65.00   Median : 0.3001  
#>  Mean   : 1.3500   Mean   :3.653   Mean   :63.87   Mean   : 0.1004  
#>  3rd Qu.: 2.1270   3rd Qu.:3.878   3rd Qu.:68.00   3rd Qu.: 1.5581  
#>  Max.   : 3.8210   Max.   :6.108   Max.   :79.00   Max.   : 2.3263  
#>       svi              lcp             gleason          pgg45       
#>  Min.   :0.0000   Min.   :-1.3863   Min.   :6.000   Min.   :  0.00  
#>  1st Qu.:0.0000   1st Qu.:-1.3863   1st Qu.:6.000   1st Qu.:  0.00  
#>  Median :0.0000   Median :-0.7985   Median :7.000   Median : 15.00  
#>  Mean   :0.2165   Mean   :-0.1794   Mean   :6.753   Mean   : 24.38  
#>  3rd Qu.:0.0000   3rd Qu.: 1.1787   3rd Qu.:7.000   3rd Qu.: 40.00  
#>  Max.   :1.0000   Max.   : 2.9042   Max.   :9.000   Max.   :100.00  
#>       lpsa        
#>  Min.   :-0.4308  
#>  1st Qu.: 1.7317  
#>  Median : 2.5915  
#>  Mean   : 2.4784  
#>  3rd Qu.: 3.0564  
#>  Max.   : 5.5829  
cor(Prostate$lpsa, Prostate$lcavol)
#> [1] 0.7344603
if (FALSE) { # \dontrun{
  fit <- islasso(lpsa ~ ., data = Prostate, family = gaussian())
  summary(fit, pval = 0.05)
  lambda.aic <- aic.islasso(fit, method = "AIC")
  fit.aic <- update(fit, lambda = lambda.aic)
  summary(fit.aic, pval = 0.05)
} # }