Remove/replace attributes from a tbl_now object

Functions that remove or replace the specified attributes of a tbl_now object.

Usage

remove_is_censored(x)

remove_strata(x, ...)

remove_all_strata(x)

remove_covariates(x, ...)

remove_all_covariates(x)

replace_temporal_effects(x, t_effects)

remove_temporal_effects(x)

Arguments

x

A tbl_now object

...

tidy-select with the columns for the attribute. In the case of covariates and strata argument ... can refer to multiple columns.

t_effects

(optional) Either NULL (default), a temporal_effects() object or a character vector with the names of the columns containing the temporal effects.

Value

A tbl_now object with updated attributes

Details

Variable selection can be used with the auxiliary dplyr verbs such as dplyr::starts_with(), dplyr::all_of(), and dplyr::where(). See dplyr::select() for additional info.

See also

add_temporal_effects() add change

Examples

data(denguedat)
ndata <- tbl_now(denguedat,
  event_date = onset_week,
  report_date = report_week,
  strata = gender,
  verbose = FALSE
)

# Add strata
ndata <- remove_strata(ndata, gender)
ndata
#> # A tibble:  52,987 × 6
#> # Data type: "linelist"
#> # Frequency: Event: `weeks` | Report: `weeks`
#>    onset_week   report_week   gender .event_num .report_num .delay
#>    <date>       <date>        <chr>       <dbl>       <dbl>  <dbl>
#>    [event_date] [report_date] [...]       [...]       [...]  [...]
#>  1 1990-01-01   1990-01-01    Male            0           0      0
#>  2 1990-01-01   1990-01-01    Female          0           0      0
#>  3 1990-01-01   1990-01-01    Female          0           0      0
#>  4 1990-01-01   1990-01-08    Female          0           1      1
#>  5 1990-01-01   1990-01-08    Male            0           1      1
#>  6 1990-01-01   1990-01-15    Female          0           2      2
#>  7 1990-01-01   1990-01-15    Female          0           2      2
#>  8 1990-01-01   1990-01-15    Female          0           2      2
#>  9 1990-01-01   1990-01-22    Female          0           3      3
#> 10 1990-01-01   1990-01-08    Female          0           1      1
#> # ────────────────────────────────────────────────────────────────────────────────
#> # Now: 2010-12-20 | Event date: "onset_week" | Report date: "report_week"
#> # ────────────────────────────────────────────────────────────────────────────────
#> # ℹ 52,977 more rows

# Change covariates
ndata$temperature <- rnorm(nrow(ndata), 25, 4)
ndata$humidity <- rbeta(nrow(ndata), 0.6, 0.4)
ndata <- ndata |> add_covariates(temperature, humidity)
ndata
#> # A tibble:  52,987 × 8
#> # Data type: "linelist"
#> # Frequency: Event: `weeks` | Report: `weeks`
#>    onset_week   report_week   gender .event_num .report_num .delay temperature
#>    <date>       <date>        <chr>       <dbl>       <dbl>  <dbl>       <dbl>
#>    [event_date] [report_date] [...]       [...]       [...]  [...] [covariate]
#>  1 1990-01-01   1990-01-01    Male            0           0      0        26.9
#>  2 1990-01-01   1990-01-01    Female          0           0      0        20.0
#>  3 1990-01-01   1990-01-01    Female          0           0      0        22.2
#>  4 1990-01-01   1990-01-08    Female          0           1      1        30.1
#>  5 1990-01-01   1990-01-08    Male            0           1      1        30.2
#>  6 1990-01-01   1990-01-15    Female          0           2      2        20.3
#>  7 1990-01-01   1990-01-15    Female          0           2      2        17.6
#>  8 1990-01-01   1990-01-15    Female          0           2      2        26.2
#>  9 1990-01-01   1990-01-22    Female          0           3      3        23.6
#> 10 1990-01-01   1990-01-08    Female          0           1      1        26.3
#> # ────────────────────────────────────────────────────────────────────────────────
#> # Now: 2010-12-20 | Event date: "onset_week" | Report date: "report_week"
#> # Covariates: "temperature" and "humidity"
#> # ────────────────────────────────────────────────────────────────────────────────
#> # ℹ 52,977 more rows
#> # ℹ 1 more variable: humidity <dbl>

ndata |> remove_covariates(temperature, humidity)
#> # A tibble:  52,987 × 8
#> # Data type: "linelist"
#> # Frequency: Event: `weeks` | Report: `weeks`
#>    onset_week   report_week   gender .event_num .report_num .delay temperature
#>    <date>       <date>        <chr>       <dbl>       <dbl>  <dbl>       <dbl>
#>    [event_date] [report_date] [...]       [...]       [...]  [...]       [...]
#>  1 1990-01-01   1990-01-01    Male            0           0      0        26.9
#>  2 1990-01-01   1990-01-01    Female          0           0      0        20.0
#>  3 1990-01-01   1990-01-01    Female          0           0      0        22.2
#>  4 1990-01-01   1990-01-08    Female          0           1      1        30.1
#>  5 1990-01-01   1990-01-08    Male            0           1      1        30.2
#>  6 1990-01-01   1990-01-15    Female          0           2      2        20.3
#>  7 1990-01-01   1990-01-15    Female          0           2      2        17.6
#>  8 1990-01-01   1990-01-15    Female          0           2      2        26.2
#>  9 1990-01-01   1990-01-22    Female          0           3      3        23.6
#> 10 1990-01-01   1990-01-08    Female          0           1      1        26.3
#> # ────────────────────────────────────────────────────────────────────────────────
#> # Now: 2010-12-20 | Event date: "onset_week" | Report date: "report_week"
#> # ────────────────────────────────────────────────────────────────────────────────
#> # ℹ 52,977 more rows
#> # ℹ 1 more variable: humidity <dbl>