uses a table, list of categories, list of summaries, list of events, and person-year information to generate person-time tables

Event_Time_Gen generates event-time tables

Usage

Event_Time_Gen(table, pyr, categ, summaries, events, verbose = FALSE)

Arguments

table

dataframe with every category/event column needed

pyr

list with entry and exit lists, containing day/month/year columns in the table

categ

list with category columns and methods, methods can be either strings or lists of boundaries, includes a time category or entry/exit are both required for the pyr list

summaries

list of columns to summarize, supports counts, means, and weighted means by person-year and renaming the summary column

events

list of events or interests, checks if events are within each time interval

verbose

integer valued 0-4 controlling what information is printed to the terminal. Each level includes the lower levels. 0: silent, 1: errors printed, 2: warnings printed, 3: notes printed, 4: debug information printed. Errors are situations that stop the regression, warnings are situations that assume default values that the user might not have intended, notes provide information on regression progress, and debug prints out C++ progress and intermediate results. The default level is 2 and True/False is converted to 3/0.

Value

returns a grouped table and a list of category boundaries used

See also

Other Data Cleaning Functions: Check_Dupe_Columns(), Check_Trunc(), Check_Verbose(), Convert_Model_Eq(), Correct_Formula_Order(), Date_Shift(), Def_Control(), Def_Control_Guess(), Def_model_control(), Def_modelform_fix(), Event_Count_Gen(), Joint_Multiple_Events(), Replace_Missing(), Time_Since(), factorize(), factorize_par(), gen_time_dep(), interact_them()

Examples

library(data.table)
a <- c(0, 1, 2, 3, 4, 5, 6)
b <- c(1, 2, 3, 4, 5, 6, 7)
c <- c(0, 1, 0, 0, 0, 1, 0)
d <- c(1, 2, 3, 4, 5, 6, 7)
e <- c(2, 3, 4, 5, 6, 7, 8)
f <- c(
  1900, 1900, 1900, 1900,
  1900, 1900, 1900
)
g <- c(1, 2, 3, 4, 5, 6, 7)
h <- c(2, 3, 4, 5, 6, 7, 8)
i <- c(
  1901, 1902, 1903, 1904,
  1905, 1906, 1907
)
table <- data.table::data.table(
  "a" = a, "b" = b, "c" = c,
  "d" = d, "e" = e, "f" = f,
  "g" = g, "h" = h, "i" = i
)
categ <- list(
  "a" = "-1/3/5]7",
  "b" = list(
    lower = c(-1, 3, 6), upper = c(3, 6, 10),
    name = c("low", "medium", "high")
  ),
  "time AS time" = list(
    "day" = c(1, 1, 1, 1, 1),
    "month" = c(1, 1, 1, 1, 1),
    "year" = c(1899, 1903, 1910)
  )
)
summary <- list(
  "c" = "count AS cases",
  "a" = "mean",
  "b" = "weighted_mean"
)
events <- list("c")
pyr <- list(
  entry = list(year = "f", month = "e", day = "d"),
  exit = list(year = "i", month = "h", day = "g"),
  unit = "years"
)
e <- Event_Time_Gen(table, pyr, categ, summary, events, T)