diff --git a/RWE_Summer_School/example.mock_data.R b/RWE_Summer_School/example.mock_data.R
new file mode 100644
index 0000000..2d42cd1
--- /dev/null
+++ b/RWE_Summer_School/example.mock_data.R
@@ -0,0 +1,132 @@
+#### Example using a "mock" database:
+# packages -----
+library(SqlRender)
+library(DatabaseConnector)
+library(CohortGenerator)
+library(CirceR)
+library(FeatureExtraction)
+library(here)
+library(lubridate)
+library(stringr)
+library(ggplot2)
+library(DBI)
+library(dbplyr)
+library(dplyr)
+library(tidyr)
+library(kableExtra)
+library(RSQLite)
+library(rmarkdown)
+library(tableone)
+library(scales)
+library(forcats)
+library(epiR)
+library(RPostgreSQL)
+library(readxl)
+library(lubridate)
+library(readxl)
+library(dtplyr)
+library(duckdb)
+devtools::load_all()
+
+
+
+
+# 0. Create a Duckdb mock database directly from R-----
+db <- duckdb::dbConnect(duckdb::duckdb(), ":memory:")
+
+person<-tibble(person_id=c("1", "2", "3", "4", "5"),
+               gender_concept_id=c("8507","8507", "8532", "8532", "8507"),
+               year_of_birth=c(2000,2010, 2003, 2001, 2012),
+               month_of_birth=c(01,10,04,06,11),
+               day_of_birth=c(01, 01, 01,01,01))
+
+observation_period<-tibble(observation_period_id=c("1","1", "1","1", "1"),
+                           person_id=c("1", "2", "3", "4", "5"),
+                           observation_period_start_date=c(as.Date("2010-01-01"),as.Date("2010-10-10"), as.Date("2012-01-01"), as.Date("2014-01-01"), as.Date("2012-12-01")),
+                           observation_period_end_date=c(as.Date("2010-06-01"),as.Date("2012-12-31"), as.Date("2014-03-01"), as.Date("2015-11-01"), as.Date("2013-02-01")))
+outcome<-tibble(cohort_definition_id=c ("1", "1","1", "1"),
+                subject_id=c("1","1", "3", "4"),
+                cohort_start_date=c(as.Date("2010-02-05"),
+                                    as.Date("2010-02-08"),
+                                    as.Date("2010-02-20"),
+                                    as.Date("2008-02-05")),
+                cohort_end_date=c(as.Date("2010-02-05"),
+                                  as.Date("2010-02-08"),
+                                  as.Date("2010-02-20"),
+                                  as.Date("2008-02-05")))
+
+DBI::dbWithTransaction(db, {
+  DBI::dbWriteTable(db, "person", person,
+                    overwrite = TRUE)
+})
+DBI::dbWithTransaction(db, {
+  DBI::dbWriteTable(db, "observation_period", observation_period,
+                    overwrite = TRUE
+  )
+})
+DBI::dbWithTransaction(db, {
+  DBI::dbWriteTable(db, "outcome", outcome,
+                    overwrite = TRUE
+  )
+})
+
+# Check how the tables look like
+dbReadTable(db, "person")
+dbReadTable(db, "observation_period")
+dbReadTable(db, "outcome")
+
+rm(person, outcome, observation_period)
+
+
+# 1. Identify the denominator population-------------
+dpop<-collect_denominator_pops(db=db,
+                                cdm_database_schema=NULL)
+#If we don't specify further specifications, all the population and all the observation time is included
+#Default arguments include: age from 0 to 150 years; both sexes; no prior history required.
+
+
+#Time periods can be specified
+dpop_time<-collect_denominator_pops(db=db,
+                               cdm_database_schema=NULL,
+                               study_start_date= as.Date("2010-01-01"),
+                               study_end_date= as.Date("2012-12-31",
+                               verbose= FALSE))
+
+#We can add further specifications in terms of age, sex, and prior history requirement.
+dpop_option<-collect_denominator_pops(db=db,
+                                      cdm_database_schema=NULL,
+                                      study_start_date= as.Date("2010-01-01"),
+                                      study_end_date= as.Date("2012-12-31"),
+                                      study_age_stratas=list(c(10,18)), #List indicating the age groups to be considered
+                                      study_sex_stratas=c("Both"),  #Vector with the stratifications in which results are desired
+                                      study_days_prior_history =0, #Number of days of prior history required.
+                                      verbose= FALSE)
+
+#More than one option for each characteristic is allowed
+dpop_mult.options<-collect_denominator_pops(db=db,
+                                    cdm_database_schema=NULL,
+                                    study_start_date= as.Date("2010-01-01"),
+                                    study_end_date= as.Date("2012-12-31"),
+                                    study_age_stratas=list(c(10,18), c(10,15)), #List indicating the age groups to be considered
+                                    study_sex_stratas=c("Both", "Female", "Male"),  #Vector with the stratifications in which results are desired
+                                    study_days_prior_history =c(0,30, 365),#Number of days of prior history required.
+                                    verbose=FALSE)
+
+
+# 2 Calculate incidence rates (IR) based on the denominator population----------
+ir<-collect_pop_incidence(db=db, #not working?????
+                          results_schema_outcomes=NULL,
+                          cohort_ids_outcomes=1,
+                          study_denominator_pop=dpop_mult.options,
+                          cohort_ids_denominator_pops= c("1"),
+                          time_intervals=c("Months"),
+                          prior_event_lookbacks = 0,
+                          confidence_intervals="exact",
+                          repetitive_events = FALSE,
+                          verbose= FALSE)
+
+
+
+
+
+