crt_combined.RdFunction which takes in trial parameters for main population modelling results and both control and intervention clusters, and runs
crt_combined( mainpop_data = list(), n_clusters = 1, n_patients = 1, benchmark = "EIR_annual", age_start = 0, age_end = 65, test_time_values = c(0, 1), test_type = "RDT", flag_pre_clearing = 0, censor_period = 0, flag_reactive_treatment = 1, prop_T_c = 0.9, benchmark_mean = 0, benchmark_stdev = 0, int_mean = 0, int_stdev = 0, data_level = "Both" )
| mainpop_data | List containing main population data output by mainpop() |
|---|---|
| n_clusters | Number of clusters (control and intervention) |
| n_patients | Number of patients per cluster |
| benchmark | Benchmark type to use in choosing clusters ("EIR", "slide_prev", "pcr_prev", or "clin_inc" for new data, "EIR_annual", "slide_prev_annual", "pcr_prev_annual", "clin_inc_annual" for pre-existing annual data in input folder) |
| age_start | Starting age to use when calculating prevalence or incidence over age range (not used with EIR) |
| age_end | End age to use when calculating prevalence or incidence over age range (not used with EIR) |
| test_time_values | Time points at which tests are administered |
| test_type | Type of test administered ("clin" = clinical, "RDT" = rapid diagnostic test) |
| flag_pre_clearing | Integer indicating whether patients given pre-trial prophylaxis (if 1, place all patients into prophylaxis category at start) |
| censor_period | Time period after a positive test during which a patient is not counted towards incidence |
| flag_reactive_treatment | Integer indicating whether patients are automatically given prophylaxis after a positive test (shifting them into treatment category if a clinical case, prophylaxis category otherwise) |
| prop_T_c | Treatment probability |
| benchmark_mean | Mean of benchmark value distribution |
| benchmark_stdev | Standard deviation of benchmark value distribution |
| int_mean | Mean of intervention parameter value distribution |
| int_stdev | Standard deviation of intervention parameter value distribution |
| data_level | Data type to output ("Cluster", "Individual" or "Both") |
Takes a list of parameters, returns output data as list