asir | R Documentation |
Calculate age-standardized incidence rates
asir( df, dattype = NULL, std_pop = "ESP2013", truncate_std_pop = FALSE, futime_src = "refpop", summarize_groups = "none", count_var, stdpop_df = standard_population, refpop_df = population, region_var = NULL, age_var = NULL, sex_var = NULL, year_var = NULL, site_var = NULL, futime_var = NULL, pyar_var = NULL, alpha = 0.05 )
df |
dataframe in wide format |
dattype |
can be "zfkd" or "seer" or NULL. Will set default variable names if dattype is "seer" or "zfkd". Default is NULL. |
std_pop |
can be either "ESP2013, ESP1976, WHO1960 |
truncate_std_pop |
if TRUE standard population will be truncated for all age-groups that do not occur in df |
futime_src |
can be either "refpop" or "cohort". Default is "refpop". |
summarize_groups |
option to define summarizing stratified groups. Default is "none". If you want to define variables that should be summarized into one group, you can chose from region_var, sex_var, year_var. Define multiple summarize variables by summarize_groups = c("region", "sex", "year") |
count_var |
variable to be counted as observed case. Should be 1 for case to be counted. |
stdpop_df |
df where standard population is defined. It is assumed that stdpop_df has the columns "sex" for biological sex, "age" for age-groups, "standard_pop" for name of standard population (e.g. "European Standard Population 2013) and "population_n" for size of standard population age-group. stdpop_df must use the same category coding of age and sex as age_var and sex_var. |
refpop_df |
df where reference population data is defined. Only required if option futime = "refpop" is chosen. It is assumed that refpop_df has the columns "region" for region, "sex" for biological sex, "age" for age-groups (can be single ages or 5-year brackets), "year" for time period (can be single year or 5-year brackets), "population_pyar" for person-years at risk in the respective age/sex/year cohort. refpop_df must use the same category coding of age, sex, region, year and site as age_var, sex_var, region_var, year_var and site_var. |
region_var |
variable in df that contains information on region where case was incident. Default is set if dattype is given. |
age_var |
variable in df that contains information on age-group. Default is set if dattype is given. |
sex_var |
variable in df that contains information on biological sex. Default is set if dattype is given. |
year_var |
variable in df that contains information on year or year-period when case was incident. Default is set if dattype is given. |
site_var |
variable in df that contains information on ICD code of case diagnosis. Default is set if dattype is given. |
futime_var |
variable in df that contains follow-up time per person (in years) in cohort (can only be used with futime_src = "cohort"). Default is set if dattype is given. |
pyar_var |
variable in refpop_df that contains person-years-at-risk in reference population (can only be used with futime_src = "refpop") Default is set if dattype is given. |
alpha |
significance level for confidence interval calculations. Default is alpha = 0.05 which will give 95 percent confidence intervals. |
df
#load sample data data("us_second_cancer") data("standard_population") data("population_us") #make wide data as this is the required format usdata_wide <- us_second_cancer %>% #only use sample dplyr::filter(as.numeric(fake_id) < 200000) %>% msSPChelpR::reshape_wide_tidyr(case_id_var = "fake_id", time_id_var = "SEQ_NUM", timevar_max = 2) #create count variable usdata_wide <- usdata_wide %>% dplyr::mutate(count_spc = dplyr::case_when(is.na(t_site_icd.2) ~ 1, TRUE ~ 0)) #remove cases for which no reference population exists usdata_wide <- usdata_wide %>% dplyr::filter(t_yeardiag.2 %in% c("1990 - 1994", "1995 - 1999", "2000 - 2004", "2005 - 2009", "2010 - 2014")) #now we can run the function msSPChelpR::asir(usdata_wide, dattype = "seer", std_pop = "ESP2013", truncate_std_pop = FALSE, futime_src = "refpop", summarize_groups = "none", count_var = "count_spc", refpop_df = population_us, region_var = "registry.1", age_var = "fc_agegroup.1", sex_var = "sex.1", year_var = "t_yeardiag.2", site_var = "t_site_icd.2", pyar_var = "population_pyar")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.