Lung

Data from a randomised trial of two treatment regimens for
  lung cancer. This is a standard survival analysis data set from the
  classic textbook by Kalbfleisch and Prentice.
  <ul><li>X: A design matrix with 137 observations (rows) and 9
    predictor variables (columns).  The columns are:<ul><li>trt: Treatment indicator (1=control group, 2=treatment
      group)</li><li>karno: Karnofsky performance score (0=bad, 100=good)</li><li>diagtime: Time from diagnosis to randomization (months)</li><li>age: Age (years)</li><li>prior: Prior therapy (0=no, 1=yes)</li><li>squamous: Indicator for whether the cancer type is squamous
      cell carcinoma (0=no, 1=yes)</li><li>small: Indicator for whether the cancer type is small cell
      lung cancer (0=no, 1=yes)</li><li>adeno: Indicator for whether the cancer type is
      adenocarcinoma (0=no, 1=yes)</li><li>large: Indicator for whether the cancer type is large cell
      carcinoma (0=no, 1=yes)</li></ul></li><li>y: A two column matrix (<code>Surv</code>object) containing the
    follow-up time (in days) and an indicator variable for whether the
    patient died while on the study or not.</li></ul>

datasets

Efficient algorithms for fitting regularization paths for linear or logistic regression models penalized by MCP or SCAD, with optional additional L2 penalty.

Patrick Breheny

ncvreg

Regularization Paths for SCAD and MCP Penalized Regression
        Models

Lung function

A list containing the design matrix <code>X</code> and response matrix
  <code>y</code>

format

<url>http://CRAN.R-project.org/package=survival</url>

Lung: VA lung cancer data set

Description

Usage

Arguments

format

source

References

See Also