# Performs basic Cox Proportional Hazards regression with a multiplicative log-linear model `RunCoxRegression_Basic` uses user provided data, time/event columns, vectors specifying the model, and options to control the convergence and starting positions ```r RunCoxRegression_Basic( df, time1 = "start", time2 = "end", event0 = "event", names = c("CONST"), keep_constant = c(0), a_n = c(0), der_iden = 0, control = list() ) ``` ## Arguments - `df`: a data.table containing the columns of interest - `time1`: column used for time period starts - `time2`: column used for time period end - `event0`: column used for event status - `names`: columns for elements of the model, used to identify data columns - `keep_constant`: binary values to denote which parameters to change - `a_n`: list of initial parameter values, used to determine number of parameters. May be either a list of vectors or a single vector. - `der_iden`: number for the subterm to test derivative at, only used for testing runs with a single varying parameter, should be smaller than total number of parameters. indexed starting at 0 - `control`: list of parameters controlling the convergence, see Def_Control() for options or vignette("Control_Options") ## Returns returns a list of the final results ## Examples ```r library(data.table) ## basic example code reproduced from the starting-description vignette df <- data.table::data.table( "UserID" = c(112, 114, 213, 214, 115, 116, 117), "Starting_Age" = c(18, 20, 18, 19, 21, 20, 18), "Ending_Age" = c(30, 45, 57, 47, 36, 60, 55), "Cancer_Status" = c(0, 0, 1, 0, 1, 0, 0), "a" = c(0, 1, 1, 0, 1, 0, 1), "b" = c(1, 1.1, 2.1, 2, 0.1, 1, 0.2), "c" = c(10, 11, 10, 11, 12, 9, 11), "d" = c(0, 0, 0, 1, 1, 1, 1) ) # For the interval case time1 <- "Starting_Age" time2 <- "Ending_Age" event <- "Cancer_Status" names <- c("a", "b", "c", "d") a_n <- c(1.1, -0.1, 0.2, 0.5) # used to test at a specific point keep_constant <- c(0, 0, 0, 0) der_iden <- 0 control <- list( "ncores" = 2, "lr" = 0.75, "maxiter" = 5, "halfmax" = 5, "epsilon" = 1e-3, "deriv_epsilon" = 1e-3, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = FALSE, "ties" = "breslow", "double_step" = 1 ) e <- RunCoxRegression_Basic( df, time1, time2, event, names, keep_constant, a_n, der_iden, control ) ``` ## See Also Other Cox Wrapper Functions: `RunCoxNull()`, `RunCoxRegression()`, `RunCoxRegression_CR()`, `RunCoxRegression_Guesses_CPP()`, `RunCoxRegression_Omnibus()`, `RunCoxRegression_Omnibus_Multidose()`, `RunCoxRegression_STRATA()`, `RunCoxRegression_Single()`, `RunCoxRegression_Tier_Guesses()`

RunCoxRegression_Basic function