tidy.felm {broom} | R Documentation

## Tidy a(n) felm 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 'felm'
    tidy(x, conf.int = FALSE, conf.level = 0.95,
      fe = FALSE, ...)

### Arguments

`x` | A `felm` object returned from `lfe::felm()`.
`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.
`fe` | Logical indicating whether or not to include estimates of fixed effects. 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 for each term in the regression. The tibble has columns:

`term` | The name of the regression term.
`estimate` | The estimated value of the regression term.
`std.error` | The standard error of the regression term.
`statistic` | The value of a statistic, almost always a T-statistic, to use in a hypothesis that the regression term is non-zero.
`p.value` | The two-sided p-value associated with the observed statistic.
`conf.low` | The low end of a confidence interval for the regression term. Included only if `conf.int = TRUE`.
`conf.high` | The high end of a confidence interval for the regression term. Included only if `conf.int = TRUE`.

If `fe = TRUE`, also includes rows for for fixed effects estimates.

### See Also

`tidy()`, `lfe::felm()`

Other felm tidiers: `augment.felm`

### Examples

    if (require("lfe", quietly = TRUE)) {

        library(lfe)

        N=1e2
        DT <- data.frame(
          id = sample(5, N, TRUE),
          v1 =  sample(5, N, TRUE),
          v2 =  sample(1e6, N, TRUE),
          v3 =  sample(round(runif(100,max=100),4), N, TRUE),
          v4 =  sample(round(runif(100,max=100),4), N, TRUE)
        )

        result_felm <- felm(v2~v3, DT)
        tidy(result_felm)
        augment(result_felm)
        result_felm <- felm(v2~v3|id+v1, DT)
        tidy(result_felm, fe = TRUE)
        augment(result_felm)
        v1<-DT$v1
        v2 <- DT$v2
        v3 <- DT$v3
        id <- DT$id
        result_felm <- felm(v2~v3|id+v1)
        tidy(result_felm)
        augment(result_felm)
        glance(result_felm)
    }

[Package broom version 0.5.2 Index]