Event_Time_Gen {Colossus} | R Documentation |
uses a table, list of categories, list of summaries, list of events, and person-year information to generate person-time tables
Description
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)