Description Usage Arguments Details Value Author(s) References See Also Examples

Provides estimate of AFT model with log logistic distribution using MCMC for multivariable (maximum 5 covariates of column at a time) in high dimensional gene expression data. It also deals covariates with missing values.

1 |

`m` |
Starting column number of covariates of study from high dimensional entered data. |

`n` |
Ending column number of covariates of study from high dimensional entered data. |

`STime` |
name of survival time in data. |

`Event` |
name of event in data. 0 is for censored and 1 for occurrence of event. |

`nc` |
number of MCMC chain. |

`ni` |
number of MCMC iteration to update the outcome. |

`data` |
High dimensional gene expression data that contains event status, survival time and and set of covariates. |

This function deals covariates (in data) with missing values. Missing value in any column (covariate) is replaced by mean of that particular covariate.
AFT model is log-linear regression model for survival time * T_1*,* T_{2}*,..,*T_{n}*.
i.e.,

*log(T_i)= x_i'β +σε_i ;~ε_i \sim F_ε (.)~which~is~iid *

Where * F_ε * is known cdf which is defined on real line.
When baseline distribution is logistic then T follows log logistic distribution.

* T \sim Log-Logis(x'β,√{τ)} *

Data frame is containing mean, sd, n.eff, Rhat and credible intervals (2.5%, 25%, 50%, 75% and 97.5%) for beta's, sigma, tau and deviance of the model for the selected covariates. beta[1] is for intercept and others are for covariates (which is/are chosen as columns in data). sigma is the scale parameter of the distribution.

Atanu Bhattacharjee, Gajendra Kumar Vishwakarma and Pragya Kumari

Prabhash et al(2016) <doi: 10.21307/stattrans-2016-046>

wbysmv, lgnbymv, lgstbyuni

1 2 3 4 |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.