This function allows you to define a minimum number of
waves/periods and exclude all individuals with fewer observations than
that.

complete_data(data, ..., formula = NULL, vars = NULL, min.waves = "all")

## Arguments

data |
A `panel_data()` frame. |

... |
Optionally, unquoted variable names/expressions separated by
commas to be passed to `dplyr::select()` . Otherwise, all columns are
included if `formula` and `vars` are also NULL. |

formula |
A formula, like the one you'll be using to specify your model. |

vars |
As an alternative to formula, a vector of variable names. |

min.waves |
What is the minimum number of observations to be kept?
Default is `"all"` , but it can be any number. |

## Value

A `panel_data`

frame.

## Details

If `...`

(that is, unquoted variable name(s)) are included, then `formula`

and `vars`

are ignored. Likewise, `formula`

takes precedence over `vars`

.
These are just different methods for selecting variables and you can choose
whichever you prefer/are comfortable with. `...`

corresponds with the
"tidyverse" way, `formula`

is useful for programming or working with
model formulas, and `vars`

is a "standard" evaluation method for when you
are working with strings.

## Examples

#> # Panel data: 4,165 x 14
#> # entities: id [595]
#> # wave variable: t [1, 2, 3, ... (7 waves)]
#> id t exp wks occ ind south smsa ms fem union ed blk
#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 3 32 0 0 1 0 1 0 0 9 0
#> 2 1 2 4 43 0 0 1 0 1 0 0 9 0
#> 3 1 3 5 40 0 0 1 0 1 0 0 9 0
#> 4 1 4 6 39 0 0 1 0 1 0 0 9 0
#> 5 1 5 7 42 0 1 1 0 1 0 0 9 0
#> 6 1 6 8 35 0 1 1 0 1 0 0 9 0
#> 7 1 7 9 32 0 1 1 0 1 0 0 9 0
#> 8 2 1 30 34 1 0 0 0 1 0 0 11 0
#> 9 2 2 31 27 1 0 0 0 1 0 0 11 0
#> 10 2 3 32 33 1 1 0 0 1 0 1 11 0
#> # ... with 4,155 more rows, and 1 more variable: lwage <dbl>