R: Tidiers for a parametric regression survival model

survreg_tidiers {broom} | R Documentation

## Tidiers for a parametric regression survival model

### Description

Tidies the coefficients of a parametric survival regression model, from the "survreg" function, adds fitted values and residuals, or summarizes the model statistics.

### Usage

    ## S3 method for class 'survreg'
    tidy(x, conf.level = 0.95, ...)

    ## S3 method for class 'survreg'
    augment(x, data = stats::model.frame(x), newdata,
      type.predict = "response", type.residuals = "response", ...)

    ## S3 method for class 'survreg'
    glance(x, conf.level = 0.95, ...)

### Arguments

`x` | a "survreg" model
`conf.level` | confidence level for CI
`...` | extra arguments (not used)
`data` | original data; if it is not provided, it is reconstructed as best as possible with `model.frame`
`newdata` | New data to use for prediction; optional
`type.predict` | type of prediction, default "response"
`type.residuals` | type of residuals to calculate, default "response"

### Details

When the modeling was performed with `na.action = "na.omit"` (as is the typical default), rows with NA in the initial data are omitted entirely from the augmented data frame. When the modeling was performed with `na.action = "na.exclude"`, one should provide the original data as a second argument, at which point the augmented data will contain those rows (typically with NAs in place of the new columns). If the original data is not provided to `augment` and `na.action = "na.exclude"`, a warning is raised and the incomplete rows are dropped.

### Value

All tidying methods return a data.frame without rownames, whose structure depends on the method chosen.

`tidy` returns a data.frame with one row for each term

`term` | name of term
`estimate` | estimate of coefficient
`stderror` | standard error
`statistic` | Z statistic
`p.value` | p-value
`conf.low` | low end of confidence interval
`conf.high` | high end of confidence interval

`augment` returns the original data.frame with the following additional columns:

`.fitted` | Fitted values of model
`.se.fit` | Standard errors of fitted values
`.resid` | Residuals

`glance` returns a one-row data.frame with the columns:

`iter` | number of iterations
`df` | degrees of freedom
`statistic` | chi-squared statistic
`p.value` | p-value from chi-squared test
`logLik` | log likelihood
`AIC` | Akaike information criterion
`BIC` | Bayesian information criterion
`df.residual` | residual degrees of freedom

### See Also

na.action

### Examples

    if (require("survival", quietly = TRUE)) {
        sr <- survreg(Surv(futime, fustat) ~ ecog.ps + rx, ovarian,
               dist="exponential")

        td <- tidy(sr)
        augment(sr, ovarian)
        augment(sr)
        glance(sr)

        # coefficient plot
        library(ggplot2)
        ggplot(td, aes(estimate, term)) + geom_point() +
            geom_errorbarh(aes(xmin = conf.low, xmax = conf.high), height = 0) +
            geom_vline(xintercept = 0)
    }

[Package broom version 0.4.4 Index]