Count FCDS Cases — count

Helper function to count cancer cases in the FCDS data by year and age group, in addition to any groups already present in the data. For convenience, you may additionally filter to include particular values of sex, race, year, county name and hispanic ethnicity. See fcds_const() for more information about possible values for these variables. By default, count_fcds() ensures that age_group, year_group, and year are included in the grouping variables if they are present in the data. If they are not, or if they are not present in the FCDS data, then it would be better to use dplyr::count() directly.

count_fcds(data, ..., sex = NULL, race = NULL, origin = NULL,
  county_name = NULL, default_groups = c("year_group", "year",
  "age_group"), discard_unseen_levels = TRUE,
  moffitt_catchment = FALSE)

Arguments

data	A data frame
...	Unquoted column names to be added to the grouping of the output and subsequent counting.
sex	Character vector of values of `sex` to be included in count, or `TRUE` to include all values of `sex` present in input data
race	Character vector of values of `race` to be included in count, or `TRUE` to include all values of `race` present in input data
origin	Character vector of values of `origin` to be included in count, or `TRUE` to include all values of `origin` present in input data
county_name	Character vector of values of `county_name` to be included in count, or `TRUE` to include all values of `county_name` present in the input data, or `"moffitt"` to limit to the counties in the catchment area of the Moffitt Cancer Center.
default_groups	Variables that should be included in the grouping, prior to counting cancer cases. Set to `NULL` to use only the groups already present in the input data.
discard_unseen_levels	If `TRUE`, drops factor levels that don't appear in the results. If `FALSE`, then no changes are made to the factor levels. If a character string of column names, then only unobserved levels in those columns are dropped.
moffitt_catchment	Deprecated. Please use `county_name = "moffitt"` instead to limit counties to those in the catchment area of the Moffitt Cancer Center.

Value

A grouped data frame with counts. The output groups includes the union of the groups of the original input data, the groups specified by the columns indicated in ..., and the default_groups added by count_fcds() (modifyable by the default_groups argument).

All factor levels will be modified to include only those levels that appear in the final output across all groups.

Examples


fcds_example %>%
  dplyr::filter(county_name == "Pinellas") %>%
  count_fcds(cancer_site_group, sex = "Male", county_name = TRUE) %>%
  head()
#> # A tibble: 6 x 7
#> # Groups:   cancer_site_group, county_name, sex, year_group, year, age_group
#> #   [6]
#>   cancer_site_group       county_name sex   year_group year  age_group     n
#>   <fct>                   <fct>       <fct> <fct>      <chr> <fct>     <int>
#> 1 Oral Cavity and Pharynx Pinellas    Male  1992-1996  1994  0 - 4         1
#> 2 Oral Cavity and Pharynx Pinellas    Male  1992-1996  1994  55 - 59       1
#> 3 Oral Cavity and Pharynx Pinellas    Male  1997-2001  1999  70 - 74       1
#> 4 Oral Cavity and Pharynx Pinellas    Male  2002-2006  2004  15 - 19       1
#> 5 Oral Cavity and Pharynx Pinellas    Male  2002-2006  2004  75 - 79       1
#> 6 Oral Cavity and Pharynx Pinellas    Male  2007-2011  2009  70 - 74       2

fcds_example %>%
  filter_age_groups(age_gt = 20, age_lt = 25) %>%
  count_fcds(sex = TRUE, county_name = c("Pinellas", "Hillsborough"))
#> # A tibble: 10 x 6
#> # Groups:   sex, county_name, year_group, year, age_group [10]
#>    sex     county_name  year_group year  age_group     n
#>    <fct>   <fct>        <fct>      <chr> <fct>     <int>
#>  1 Male    Pinellas     1992-1996  1994  20 - 24       1
#>  2 Male    Pinellas     2002-2006  2004  20 - 24       2
#>  3 Male    Pinellas     2007-2011  2009  20 - 24       2
#>  4 Female  Hillsborough 1992-1996  1994  20 - 24       3
#>  5 Female  Hillsborough 2007-2011  2009  20 - 24       1
#>  6 Female  Hillsborough 2012-2016  2014  20 - 24       1
#>  7 Female  Pinellas     1987-1991  1989  20 - 24       1
#>  8 Female  Pinellas     2007-2011  2009  20 - 24       2
#>  9 Unknown Hillsborough 2002-2006  2004  20 - 24       1
#> 10 Unknown Pinellas     1997-2001  1999  20 - 24       1

fcds_example %>%
  count_fcds(county_name = "moffitt") %>%
  head()
#> # A tibble: 6 x 5
#> # Groups:   county_name, year_group, year, age_group [6]
#>   county_name year_group year  age_group     n
#>   <fct>       <fct>      <chr> <fct>     <int>
#> 1 Charlotte   1982-1986  1984  20 - 24       1
#> 2 Charlotte   1982-1986  1984  35 - 39       1
#> 3 Charlotte   1982-1986  1984  40 - 44       1
#> 4 Charlotte   1982-1986  1984  45 - 49       1
#> 5 Charlotte   1982-1986  1984  50 - 54       2
#> 6 Charlotte   1982-1986  1984  55 - 59       5