Extract data from stata file for data dictionary
Usage
ds2dd_detailed(
data,
add.auto.id = FALSE,
date.format = "dmy",
form.name = NULL,
form.sep = NULL,
form.prefix = TRUE,
field.type = NULL,
field.label = NULL,
field.label.attr = "label",
field.validation = NULL,
metadata = names(REDCapCAST::redcapcast_meta),
convert.logicals = TRUE
)Arguments
- data
data frame
- add.auto.id
flag to add id column
- date.format
date format, character string. ymd/dmy/mdy. dafault is dmy.
- form.name
manually specify form name(s). Vector of length 1 or ncol(data). Default is NULL and "data" is used.
- form.sep
If supplied dataset has form names as suffix or prefix to the column/variable names, the seperator can be specified. If supplied, the form.name is ignored. Default is NULL.
- form.prefix
Flag to set if form is prefix (TRUE) or suffix (FALSE) to the column names. Assumes all columns have pre- or suffix if specified.
- field.type
manually specify field type(s). Vector of length 1 or ncol(data). Default is NULL and "text" is used for everything but factors, which wil get "radio".
- field.label
manually specify field label(s). Vector of length 1 or ncol(data). Default is NULL and colnames(data) is used or attribute `field.label.attr` for haven_labelled data set (imported .dta file with `haven::read_dta()`).
- field.label.attr
attribute name for named labels for haven_labelled data set (imported .dta file with `haven::read_dta()`. Default is "label"
- field.validation
manually specify field validation(s). Vector of length 1 or ncol(data). Default is NULL and `levels()` are used for factors or attribute `factor.labels.attr` for haven_labelled data set (imported .dta file with `haven::read_dta()`).
- metadata
redcap metadata headings. Default is REDCapCAST:::metadata_names.
- convert.logicals
convert logicals to factor. Default is TRUE.
Details
This function is a natural development of the ds2dd() function. It assumes that the first column is the ID-column. No checks. Please, do always inspect the data dictionary before upload.
Ensure, that the data set is formatted with as much information as possible.
`field.type` can be supplied
Examples
## Basic parsing with default options
REDCapCAST::redcapcast_data |>
dplyr::select(-dplyr::starts_with("redcap_")) |>
ds2dd_detailed()
#> $data
#> # A tibble: 25 × 24
#> record_id cpr inclusion inclusion_time dob age age_integer sex
#> <dbl> <chr> <date> <chr> <date> <dbl> <dbl> <chr>
#> 1 1 12034… 2023-03-13 12:38:49 1940-03-12 83.0 83 fema…
#> 2 2 01023… 2023-03-01 10:38:57 1934-02-01 89.1 89 male
#> 3 2 NA NA NA NA NA NA NA
#> 4 2 NA NA NA NA NA NA NA
#> 5 3 23015… 2022-03-08 12:01:07 1956-01-23 66.1 66 male
#> 6 3 NA NA NA NA NA NA NA
#> 7 3 NA NA NA NA NA NA NA
#> 8 3 NA NA NA NA NA NA NA
#> 9 3 NA NA NA NA NA NA NA
#> 10 3 NA NA NA NA NA NA NA
#> # ℹ 15 more rows
#> # ℹ 16 more variables: cohabitation <chr>, hypertension <chr>, diabetes <chr>,
#> # region <chr>, baseline_data_start_complete <chr>, mrs_assessed <chr>,
#> # mrs_date <date>, mrs_score <dbl>, mrs_complete <chr>, con_mrs <fct>,
#> # con_calc <fct>, consensus_complete <chr>, event_datetime <dttm>,
#> # event_age <dbl>, event_type <chr>, new_event_complete <chr>
#>
#> $meta
#> # A tibble: 24 × 18
#> field_name form_name section_header field_type field_label
#> <chr> <chr> <lgl> <chr> <chr>
#> 1 record_id data NA text record_id
#> 2 cpr data NA text cpr
#> 3 inclusion data NA text inclusion
#> 4 inclusion_time data NA text inclusion_time
#> 5 dob data NA text dob
#> 6 age data NA text age
#> 7 age_integer data NA text age_integer
#> 8 sex data NA text sex
#> 9 cohabitation data NA text cohabitation
#> 10 hypertension data NA text hypertension
#> # ℹ 14 more rows
#> # ℹ 13 more variables: select_choices_or_calculations <chr>, field_note <lgl>,
#> # text_validation_type_or_show_slider_number <chr>,
#> # text_validation_min <lgl>, text_validation_max <lgl>, identifier <lgl>,
#> # branching_logic <lgl>, required_field <lgl>, custom_alignment <lgl>,
#> # question_number <lgl>, matrix_group_name <lgl>, matrix_ranking <lgl>,
#> # field_annotation <lgl>
#>
#> attr(,"class")
#> [1] "REDCapCAST" "list"
## Adding a record_id field
iris |> ds2dd_detailed(add.auto.id = TRUE)
#> $data
#> # A tibble: 150 × 6
#> record_id sepal.length sepal.width petal.length petal.width species
#> <int> <dbl> <dbl> <dbl> <dbl> <fct>
#> 1 1 5.1 3.5 1.4 0.2 setosa
#> 2 2 4.9 3 1.4 0.2 setosa
#> 3 3 4.7 3.2 1.3 0.2 setosa
#> 4 4 4.6 3.1 1.5 0.2 setosa
#> 5 5 5 3.6 1.4 0.2 setosa
#> 6 6 5.4 3.9 1.7 0.4 setosa
#> 7 7 4.6 3.4 1.4 0.3 setosa
#> 8 8 5 3.4 1.5 0.2 setosa
#> 9 9 4.4 2.9 1.4 0.2 setosa
#> 10 10 4.9 3.1 1.5 0.1 setosa
#> # ℹ 140 more rows
#>
#> $meta
#> # A tibble: 6 × 18
#> field_name form_name section_header field_type field_label
#> <chr> <chr> <lgl> <chr> <chr>
#> 1 record_id data NA text record_id
#> 2 sepal.length data NA text Sepal.Length
#> 3 sepal.width data NA text Sepal.Width
#> 4 petal.length data NA text Petal.Length
#> 5 petal.width data NA text Petal.Width
#> 6 species data NA radio Species
#> # ℹ 13 more variables: select_choices_or_calculations <chr>, field_note <lgl>,
#> # text_validation_type_or_show_slider_number <chr>,
#> # text_validation_min <lgl>, text_validation_max <lgl>, identifier <lgl>,
#> # branching_logic <lgl>, required_field <lgl>, custom_alignment <lgl>,
#> # question_number <lgl>, matrix_group_name <lgl>, matrix_ranking <lgl>,
#> # field_annotation <lgl>
#>
#> attr(,"class")
#> [1] "REDCapCAST" "list"
## Passing form name information to function
iris |>
ds2dd_detailed(
add.auto.id = TRUE,
form.name = sample(c("b", "c"), size = 6, replace = TRUE, prob = rep(.5, 2))
) |>
purrr::pluck("meta")
#> # A tibble: 6 × 18
#> field_name form_name section_header field_type field_label
#> <chr> <chr> <lgl> <chr> <chr>
#> 1 record_id b NA text record_id
#> 2 sepal.length c NA text Sepal.Length
#> 3 sepal.width b NA text Sepal.Width
#> 4 petal.length c NA text Petal.Length
#> 5 petal.width b NA text Petal.Width
#> 6 species c NA radio Species
#> # ℹ 13 more variables: select_choices_or_calculations <chr>, field_note <lgl>,
#> # text_validation_type_or_show_slider_number <chr>,
#> # text_validation_min <lgl>, text_validation_max <lgl>, identifier <lgl>,
#> # branching_logic <lgl>, required_field <lgl>, custom_alignment <lgl>,
#> # question_number <lgl>, matrix_group_name <lgl>, matrix_ranking <lgl>,
#> # field_annotation <lgl>
mtcars |> ds2dd_detailed(add.auto.id = TRUE)
#> $data
#> # A tibble: 32 × 12
#> record_id mpg cyl disp hp drat wt qsec vs am gear carb
#> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
#> 7 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
#> 8 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
#> 9 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
#> 10 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
#> # ℹ 22 more rows
#>
#> $meta
#> # A tibble: 12 × 18
#> field_name form_name section_header field_type field_label
#> <chr> <chr> <lgl> <chr> <chr>
#> 1 record_id data NA text record_id
#> 2 mpg data NA text mpg
#> 3 cyl data NA text cyl
#> 4 disp data NA text disp
#> 5 hp data NA text hp
#> 6 drat data NA text drat
#> 7 wt data NA text wt
#> 8 qsec data NA text qsec
#> 9 vs data NA text vs
#> 10 am data NA text am
#> 11 gear data NA text gear
#> 12 carb data NA text carb
#> # ℹ 13 more variables: select_choices_or_calculations <lgl>, field_note <lgl>,
#> # text_validation_type_or_show_slider_number <chr>,
#> # text_validation_min <lgl>, text_validation_max <lgl>, identifier <lgl>,
#> # branching_logic <lgl>, required_field <lgl>, custom_alignment <lgl>,
#> # question_number <lgl>, matrix_group_name <lgl>, matrix_ranking <lgl>,
#> # field_annotation <lgl>
#>
#> attr(,"class")
#> [1] "REDCapCAST" "list"
## Using column name suffix to carry form name
data <- iris |>
ds2dd_detailed(add.auto.id = TRUE) |>
purrr::pluck("data")
names(data) <- glue::glue("{sample(x = c('a','b'),size = length(names(data)),
replace=TRUE,prob = rep(x=.5,2))}__{names(data)}")
data |> ds2dd_detailed(form.sep = "__")
#> $data
#> # A tibble: 150 × 6
#> record_id sepal.length sepal.width petal.length petal.width species
#> <int> <dbl> <dbl> <dbl> <dbl> <fct>
#> 1 1 5.1 3.5 1.4 0.2 setosa
#> 2 2 4.9 3 1.4 0.2 setosa
#> 3 3 4.7 3.2 1.3 0.2 setosa
#> 4 4 4.6 3.1 1.5 0.2 setosa
#> 5 5 5 3.6 1.4 0.2 setosa
#> 6 6 5.4 3.9 1.7 0.4 setosa
#> 7 7 4.6 3.4 1.4 0.3 setosa
#> 8 8 5 3.4 1.5 0.2 setosa
#> 9 9 4.4 2.9 1.4 0.2 setosa
#> 10 10 4.9 3.1 1.5 0.1 setosa
#> # ℹ 140 more rows
#>
#> $meta
#> # A tibble: 6 × 18
#> field_name form_name section_header field_type field_label
#> <chr> <chr> <lgl> <chr> <chr>
#> 1 record_id a NA text record_id
#> 2 sepal.length a NA text sepal.length
#> 3 sepal.width a NA text sepal.width
#> 4 petal.length b NA text petal.length
#> 5 petal.width b NA text petal.width
#> 6 species b NA radio species
#> # ℹ 13 more variables: select_choices_or_calculations <chr>, field_note <lgl>,
#> # text_validation_type_or_show_slider_number <chr>,
#> # text_validation_min <lgl>, text_validation_max <lgl>, identifier <lgl>,
#> # branching_logic <lgl>, required_field <lgl>, custom_alignment <lgl>,
#> # question_number <lgl>, matrix_group_name <lgl>, matrix_ranking <lgl>,
#> # field_annotation <lgl>
#>
#> attr(,"class")
#> [1] "REDCapCAST" "list"