wbysmv {afthd} | R Documentation |
Provides estimate of AFT model with weibull 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.
wbysmv(m, n, STime, Event, nc, ni, data)
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 status in data. 0 is for censored and 1 for occurrence of event. |
nc |
number of markov chain. |
ni |
number of iteration for MCMC. |
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'\beta +\sigma\epsilon_i ;~\epsilon_i \sim F_\epsilon (.)~which~is~iid
Where F_\epsilon
is known cdf which is defined on real line.
Here, when baseline distribution is extreme value then T follows weibull distribution.
To make interpretation of regression coefficients simpler, using extreme value distribution with median 0.
So using weibull distribution that leads to AFT model when
T \sim Weib(\sqrt{\tau},log(2)\exp(-x'\beta \sqrt{\tau}))
Data frame is containing mean, sd, n.eff, Rhat and credible intervals for beta's, sigma, alpha, tau and deviance of the model for the chosen 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. alpha is shape parameter of the distribution.
Atanu Bhattacharjee, Gajendra Kumar Vishwakarma and Pragya Kumari
Prabhash et al(2016) <doi:10.21307/stattrans-2016-046>
pvaft, wbysuni, rglwbysm, wbyscrkm, wbyAgmv
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data(hdata)
wbysmv(9,13,STime="os",Event="death",2,10,hdata)
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