Estimate point prevalence
estimatePointPrevalence.Rd
Estimate point prevalence
Usage
estimatePointPrevalence(
cdm,
denominatorTable,
outcomeTable,
denominatorCohortId = NULL,
outcomeCohortId = NULL,
interval = "years",
timePoint = "start",
strata = list(),
includeOverallStrata = TRUE,
minCellCount = 5,
returnParticipants = FALSE
)
Arguments
- cdm
A CDM reference object
- denominatorTable
A cohort table with a set of denominator cohorts (for example, created using the
generateDenominatorCohortSet()
function).- outcomeTable
A cohort table in the cdm reference containing a set of outcome cohorts.
- denominatorCohortId
The cohort definition ids of the denominator cohorts of interest. If NULL all cohorts will be considered in the analysis.
- outcomeCohortId
The cohort definition ids of the outcome cohorts of interest. If NULL all cohorts will be considered in the analysis.
- interval
Time intervals over which period prevalence is estimated. Can be "weeks", "months", "quarters", or "years". ISO weeks will be used for weeks. Calendar months, quarters, or years can be used as the period. If more than one option is chosen then results will be estimated for each chosen interval.
- timePoint
where to compute the point prevalence
- strata
Variables added to the denominator cohort table for which to stratify estimates.
- includeOverallStrata
Whether to include an overall result as well as strata specific results (when strata has been specified).
- minCellCount
Minimum number of events to report- results lower than this will be obscured. If NULL all results will be reported.
- returnParticipants
Either TRUE or FALSE. If TRUE references to participants from the analysis will be returned allowing for further analysis. Note, if using permanent tables and returnParticipants is TRUE, one table per analysis will be kept in the cdm write schema.
Examples
# \donttest{
cdm <- mockIncidencePrevalenceRef(sampleSize = 1000)
cdm <- generateDenominatorCohortSet(
cdm = cdm, name = "denominator",
cohortDateRange = c(as.Date("2008-01-01"), as.Date("2018-01-01"))
)
#> ℹ Creating denominator cohorts
#> ✔ Cohorts created in 0 min and 2 sec
estimatePointPrevalence(
cdm = cdm,
denominatorTable = "denominator",
outcomeTable = "outcome",
interval = "months"
)
#> Getting prevalence for analysis 1 of 1
#> Time taken: 0 mins and 0 secs
#> # A tibble: 121 × 29
#> analysis_id prevalence_start_date prevalence_end_date n_cases n_population
#> <chr> <date> <date> <int> <int>
#> 1 1 2008-01-01 2008-01-01 0 691
#> 2 1 2008-02-01 2008-02-01 NA 691
#> 3 1 2008-03-01 2008-03-01 0 690
#> 4 1 2008-04-01 2008-04-01 0 688
#> 5 1 2008-05-01 2008-05-01 0 685
#> 6 1 2008-06-01 2008-06-01 0 685
#> 7 1 2008-07-01 2008-07-01 0 684
#> 8 1 2008-08-01 2008-08-01 0 681
#> 9 1 2008-09-01 2008-09-01 0 681
#> 10 1 2008-10-01 2008-10-01 0 681
#> # ℹ 111 more rows
#> # ℹ 24 more variables: prevalence <dbl>, prevalence_95CI_lower <dbl>,
#> # prevalence_95CI_upper <dbl>, population_obscured <chr>,
#> # cases_obscured <chr>, result_obscured <chr>, outcome_cohort_id <int>,
#> # outcome_cohort_name <chr>, analysis_type <chr>, analysis_interval <chr>,
#> # analysis_complete_database_intervals <lgl>, analysis_time_point <chr>,
#> # analysis_full_contribution <lgl>, analysis_min_cell_count <dbl>, …
# }