tidy.geeglm {broom} | R Documentation

## Tidy a(n) geeglm object

### Description

Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies cross models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

### Usage

    ## S3 method for class 'geeglm'
    tidy(x, conf.int = FALSE, conf.level = 0.95,
      exponentiate = FALSE, quick = FALSE, ...)

### Arguments

`x` | A `geeglm` object returned from a call to `geepack::geeglm()`.
`conf.int` | Logical indicating whether or not to include a confidence interval in the tidied output. Defaults to `FALSE`.
`conf.level` | The confidence level to use for the confidence interval if `conf.int = TRUE`. Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval.
`exponentiate` | Logical indicating whether or not to exponentiate the the coefficient estimates. This is typical for logistic and multinomial regressions, but a bad idea if there is no log or logit link. Defaults to `FALSE`.
`quick` | Logical indiciating if the only the `term` and `estimate` columns should be returned. Often useful to avoid time consuming covariance and standard error calculations. Defaults to `FALSE`.

`...`

Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in `...`, where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass `conf.lvel = 0.9`, all computation will proceed using `conf.level = 0.95`. Additionally, if you pass `newdata = my_tibble` to an `augment()` method that does not accept a `newdata` argument, it will use the default value for the `data` argument.

### Details

If `conf.int = TRUE`, the confidence interval is computed with the an internal `confint.geeglm()` function.

If you have missing values in your model data, you may need to refit the model with `na.action = na.exclude` or deal with the missingness in the data beforehand.

### Value

A tibble::tibble with one row for each coefficient, with five columns:

`term` | The term in the linear model being estimated and tested
`estimate` | The estimated coefficient
`std.error` | The standard error from the GEE model
`statistic` | Wald statistic
`p.value` | two-sided p-value

If `conf.int = TRUE`, includes includes columns `conf.low` and `conf.high`, which are computed internally.

### See Also

`tidy()`, `geepack::geeglm()`

### Examples

    if (requireNamespace("geepack", quietly = TRUE)) {
      library(geepack)
      data(state)

      ds <- data.frame(state.region, state.x77)

      geefit <- geeglm(Income ~ Frost + Murder, id = state.region,
                       data = ds, family = gaussian,
                       corstr = "exchangeable")

      tidy(geefit)
      tidy(geefit, quick = TRUE)
      tidy(geefit, conf.int = TRUE)
    }

[Package broom version 0.5.2 Index]