tidy.btergm {broom} | R Documentation

## Tidy a(n) btergm 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.

This method tidies the coefficients of a bootstrapped temporal exponential random graph model estimated with the xergm. It simply returns the coefficients and their confidence intervals.

### Usage

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

### Arguments

`x` | A `btergm::btergm()` object.
`conf.level` | Confidence level for confidence intervals. Defaults to 0.95.
`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.

### Value

A tibble::tibble with one row per term in the random graph model and columns:

`term` | The term in the model being estimated and tested.
`estimate` | The estimated value of the coefficient.
`conf.low` | The lower bound of the confidence interval.
`conf.high` | The lower bound of the confidence interval.

### See Also

`tidy()`, `btergm::btergm()`

### Examples

    if (require("xergm")) {
        set.seed(1)
        # Using the same simulated example as the xergm package
        # Create 10 random networks with 10 actors
        networks <- list()
        for(i in 1:10){
            mat <- matrix(rbinom(100, 1, .25), nrow = 10, ncol = 10)
            diag(mat) <- 0
            nw <- network::network(mat)
            networks[[i]] <- nw
        }
        # Create 10 matrices as covariates
        covariates <- list()
        for (i in 1:10) {
            mat <- matrix(rnorm(100), nrow = 10, ncol = 10)
            covariates[[i]] <- mat
        }
        # Fit a model where the propensity to form ties depends
        # on the edge covariates, controlling for the number of
        # in-stars
        suppressWarnings(btfit <- btergm(networks ~ edges + istar(2) +
                           edgecov(covariates), R = 100))

        # Show terms, coefficient estimates and errors
        tidy(btfit)

        # Show coefficients as odds ratios with a 99% CI
        tidy(btfit, exponentiate = TRUE, conf.level = 0.99)
    }

[Package broom version 0.5.2 Index]