## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 7, fig.height = 5, eval = Sys.getenv("$RUNNER_OS") != "macOS" ) ## ----echo=FALSE, message=FALSE, out.width="80%", warning=FALSE---------------- library(knitr) library(here) knitr::include_graphics(here("vignettes/dpop1.png")) ## ----echo=FALSE, out.width="80%"---------------------------------------------- knitr::include_graphics(here("vignettes/dpop2.png")) ## ----echo=FALSE, out.width="80%"---------------------------------------------- knitr::include_graphics(here("vignettes/dpop3.png")) ## ----echo=FALSE, out.width="80%"---------------------------------------------- knitr::include_graphics(here("vignettes/dpop4.png")) ## ----message=FALSE, warning=FALSE--------------------------------------------- library(CDMConnector) library(IncidencePrevalence) library(ggplot2) library(tidyr) library(dplyr) ## ----message=TRUE------------------------------------------------------------- cdm <- mockIncidencePrevalenceRef(sampleSize = 500) ## ----message=FALSE, warning=FALSE--------------------------------------------- cdm <- generateDenominatorCohortSet( cdm = cdm, name = "denominator", cohortDateRange = as.Date(c(NA,NA)), ageGroup = list(c(0, 150)), sex = "Both", daysPriorObservation = 0 ) cdm$denominator cdm$denominator %>% filter(subject_id %in% c("1", "2", "3", "4", "5")) ## ----message=FALSE, warning=FALSE, echo=FALSE--------------------------------- cdm$denominator %>% collect() %>% filter(subject_id %in% c("1", "2", "3", "4", "5")) %>% pivot_longer(cols = c( "cohort_start_date", "cohort_end_date" )) %>% ggplot() + geom_point(aes(x = value, y = subject_id)) + geom_line(aes(x = value, y = subject_id)) + theme_minimal() + xlab("Year") ## ----message=FALSE, warning=FALSE--------------------------------------------- cdm$denominator %>% collect() %>% ggplot() + theme_minimal() + geom_histogram(aes(cohort_start_date), colour = "black", fill = "grey" ) ## ----message=FALSE, warning=FALSE--------------------------------------------- cdm$denominator %>% collect() %>% ggplot() + theme_minimal() + geom_histogram(aes(cohort_end_date), colour = "black", fill = "grey" ) ## ----message=FALSE, warning=FALSE--------------------------------------------- cdm <- generateDenominatorCohortSet( cdm = cdm, name = "denominator", cohortDateRange = c(as.Date("1990-01-01"), as.Date("2009-12-31")), ageGroup = list(c(0, 150)), sex = "Both", daysPriorObservation = 0 ) cdm$denominator cohortCount(cdm$denominator) cdm$denominator %>% filter(subject_id %in% c("1", "2", "3", "4", "5")) ## ----message=FALSE, warning=FALSE--------------------------------------------- cdm$denominator %>% collect() %>% ggplot() + theme_minimal() + geom_histogram(aes(cohort_start_date), colour = "black", fill = "grey" ) ## ----message=FALSE, warning=FALSE--------------------------------------------- cdm$denominator %>% collect() %>% ggplot() + theme_minimal() + geom_histogram(aes(cohort_end_date), colour = "black", fill = "grey" ) ## ----message=FALSE, warning=FALSE--------------------------------------------- cdm <- generateDenominatorCohortSet( cdm = cdm, name = "denominator", cohortDateRange = c(as.Date("1990-01-01"), as.Date("2009-12-31")), ageGroup = list(c(0, 150)), sex = "Both", daysPriorObservation = 365 ) cdm$denominator cohortCount(cdm$denominator) cdm$denominator %>% filter(subject_id %in% c("1", "2", "3", "4", "5")) ## ----message=FALSE, warning=FALSE--------------------------------------------- cdm <- generateDenominatorCohortSet( cdm = cdm, name = "denominator", cohortDateRange = c(as.Date("1990-01-01"), as.Date("2009-12-31")), ageGroup = list(c(18, 65)), sex = "Female", daysPriorObservation = 365 ) cdm$denominator %>% glimpse() cohortCount(cdm$denominator) cdm$denominator %>% filter(subject_id %in% c("1", "2", "3", "4", "5")) ## ----message=FALSE, warning=FALSE--------------------------------------------- cdm <- mockIncidencePrevalenceRef(sampleSize = 500, earliestObservationStartDate = as.Date("2000-01-01"), latestObservationStartDate = as.Date("2005-01-01"), minDaysToObservationEnd = 10000, maxDaysToObservationEnd = NULL, earliestDateOfBirth = as.Date("1960-01-01"), latestDateOfBirth = as.Date("1980-01-01")) cdm <- generateDenominatorCohortSet( cdm = cdm, name = "denominator", ageGroup = list( c(0, 40), c(41, 100) ), sex = "Both", daysPriorObservation = 0 ) cdm$denominator %>% filter(subject_id %in% !!as.character(seq(1:30))) %>% collect() %>% left_join(settings(cdm$denominator), by = "cohort_definition_id") %>% pivot_longer(cols = c( "cohort_start_date", "cohort_end_date" )) %>% mutate(subject_id = factor(as.numeric(subject_id))) %>% ggplot(aes(x = subject_id, y = value, colour = age_group)) + geom_point(position = position_dodge(width = 0.5)) + geom_line(position = position_dodge(width = 0.5)) + theme_minimal() + theme(legend.position = "top", legend.title = element_blank()) + ylab("Year") + coord_flip() ## ----message=FALSE, warning=FALSE, fig.height=8------------------------------- cdm <- generateDenominatorCohortSet( cdm = cdm, name = "denominator", ageGroup = list( c(0, 40), c(41, 100) ), sex = c("Male", "Female", "Both"), daysPriorObservation = 0 ) cdm$denominator %>% filter(subject_id %in% !!as.character(seq(1:15))) %>% collect() %>% left_join(settings(cdm$denominator)) %>% pivot_longer(cols = c( "cohort_start_date", "cohort_end_date" )) %>% mutate(subject_id = factor(as.numeric(subject_id))) %>% ggplot(aes(x = subject_id, y = value, colour = age_group)) + facet_grid(sex ~ ., space = "free_y") + geom_point(position = position_dodge(width = 0.5)) + geom_line(position = position_dodge(width = 0.5)) + theme_bw() + theme(legend.position = "top", legend.title = element_blank()) + ylab("Year") + coord_flip() ## ----message=FALSE, warning=FALSE, fig.height=10------------------------------ cdm <- generateDenominatorCohortSet( cdm = cdm, name = "denominator", ageGroup = list( c(0, 40), c(41, 100) ), sex = c("Male", "Female", "Both"), daysPriorObservation = c(0, 365) ) cdm$denominator %>% filter(subject_id %in% !!as.character(seq(1:8))) %>% collect() %>% left_join(cohortSet(cdm$denominator)) %>% pivot_longer(cols = c( "cohort_start_date", "cohort_end_date" )) %>% mutate(subject_id = factor(as.numeric(subject_id))) %>% ggplot(aes(x = subject_id, y = value, colour = age_group, linetype = sex, shape = sex )) + facet_grid(sex + days_prior_observation ~ ., space = "free", scales = "free") + geom_point(position = position_dodge(width = 0.5)) + geom_line(position = position_dodge(width = 0.5)) + theme_bw() + theme(legend.position = "top") + ylab("Year") + coord_flip() ## ----message=FALSE, warning=FALSE, fig.height=10------------------------------ cdm <- generateDenominatorCohortSet( cdm = cdm, name = "denominator", ageGroup = list( c(0, 40), c(41, 100) ), sex = c("Male", "Female", "Both"), daysPriorObservation = c(0, 365), requirementInteractions = FALSE ) cdm$denominator %>% filter(subject_id %in% !!as.character(seq(1:8))) %>% collect() %>% left_join(cohortSet(cdm$denominator)) %>% pivot_longer(cols = c( "cohort_start_date", "cohort_end_date" )) %>% mutate(subject_id = factor(as.numeric(subject_id))) %>% ggplot(aes(x = subject_id, y = value, colour = age_group, linetype = sex, shape = sex )) + facet_grid(sex + days_prior_observation ~ ., space = "free", scales = "free") + geom_point(position = position_dodge(width = 0.5)) + geom_line(position = position_dodge(width = 0.5)) + theme_bw() + theme(legend.position = "top") + ylab("Year") + coord_flip() ## ----message=TRUE, warning=FALSE, message=FALSE------------------------------- cdm <- generateDenominatorCohortSet( cdm = cdm, name = "denominator", cohortDateRange = c(as.Date("1990-01-01"), as.Date("2009-12-31")), ageGroup = list( c(0, 18), c(19, 100) ), sex = c("Male", "Female"), daysPriorObservation = c(0, 365) ) head(cdm$denominator, 8) ## ----message=TRUE, warning=FALSE---------------------------------------------- settings(cdm$denominator) %>% glimpse() ## ----message=TRUE, warning=FALSE---------------------------------------------- cohortCount(cdm$denominator) %>% glimpse() ## ----message=TRUE, warning=FALSE---------------------------------------------- attrition(cdm$denominator) %>% glimpse()