dreg | R Documentation |
Regression for data frames with dutility call
dreg( data, y, x = NULL, z = NULL, x.oneatatime = TRUE, x.base.names = NULL, z.arg = c("clever", "base", "group", "condition"), fun. = lm, summary. = summary, regex = FALSE, convert = NULL, doSummary = TRUE, special = NULL, equal = TRUE, test = 1, ... )
data |
data frame |
y |
name of variable, or fomula, or names of variables on data frame. |
x |
name of variable, or fomula, or names of variables on data frame. |
z |
name of variable, or fomula, or names of variables on data frame. |
x.oneatatime |
x's one at a time |
x.base.names |
base covarirates |
z.arg |
what is Z, c("clever","base","group","condition"), clever decides based on type of Z, base means that Z is used as fixed baseline covaraites for all X, group means the analyses is done based on groups of Z, and condition means that Z specifies a condition on the data |
fun. |
function lm is default |
summary. |
summary to use |
regex |
regex |
convert |
convert |
doSummary |
doSummary or not |
special |
special's |
equal |
to do pairwise stuff |
test |
development argument |
... |
Additional arguments for fun |
Klaus K. Holst, Thomas Scheike
##' data(iris) dat <- iris drename(dat) <- ~. names(dat) set.seed(1) dat$time <- runif(nrow(dat)) dat$time1 <- runif(nrow(dat)) dat$status <- rbinom(nrow(dat),1,0.5) dat$S1 <- with(dat, Surv(time,status)) dat$S2 <- with(dat, Surv(time1,status)) dat$id <- 1:nrow(dat) mm <- dreg(dat, "*.length"~"*.width"|I(species=="setosa" & status==1)) mm <- dreg(dat, "*.length"~"*.width"|species+status) mm <- dreg(dat, "*.length"~"*.width"|species) mm <- dreg(dat, "*.length"~"*.width"|species+status,z.arg="group") ## Reduce Ex.Timings y <- "S*"~"*.width" xs <- dreg(dat, y, fun.=phreg) xs <- dreg(dat, y, fun.=survdiff) y <- "S*"~"*.width" xs <- dreg(dat, y, x.oneatatime=FALSE, fun.=phreg) ## under condition y <- S1~"*.width"|I(species=="setosa" & sepal.width>3) xs <- dreg(dat, y, z.arg="condition", fun.=phreg) xs <- dreg(dat, y, fun.=phreg) ## under condition y <- S1~"*.width"|species=="setosa" xs <- dreg(dat, y, z.arg="condition", fun.=phreg) xs <- dreg(dat, y, fun.=phreg) ## with baseline after | y <- S1~"*.width"|sepal.length xs <- dreg(dat, y, fun.=phreg) ## by group by species, not working y <- S1~"*.width"|species ss <- split(dat, paste(dat$species, dat$status)) xs <- dreg(dat, y, fun.=phreg) ## species as base, species is factor so assumes that this is grouping y <- S1~"*.width"|species xs <- dreg(dat, y, z.arg="base", fun.=phreg) ## background var after | and then one of x's at at time y <- S1~"*.width"|status+"sepal*" xs <- dreg(dat, y, fun.=phreg) ## background var after | and then one of x's at at time ##y <- S1~"*.width"|status+"sepal*" ##xs <- dreg(dat, y, x.oneatatime=FALSE, fun.=phreg) ##xs <- dreg(dat, y, fun.=phreg) ## background var after | and then one of x's at at time ##y <- S1~"*.width"+factor(species) ##xs <- dreg(dat, y, fun.=phreg) ##xs <- dreg(dat, y, fun.=phreg, x.oneatatime=FALSE) y <- S1~"*.width"|factor(species) xs <- dreg(dat, y, z.arg="base", fun.=phreg) y <- S1~"*.width"|cluster(id)+factor(species) xs <- dreg(dat, y, z.arg="base", fun.=phreg) xs <- dreg(dat, y, z.arg="base", fun.=coxph) ## under condition with groups y <- S1~"*.width"|I(sepal.length>4) xs <- dreg(subset(dat, species=="setosa"), y,z.arg="group",fun.=phreg) ## under condition with groups y <- S1~"*.width"+I(log(sepal.length))|I(sepal.length>4) xs <- dreg(subset(dat, species=="setosa"), y,z.arg="group",fun.=phreg) y <- S1~"*.width"+I(dcut(sepal.length))|I(sepal.length>4) xs <- dreg(subset(dat,species=="setosa"), y,z.arg="group",fun.=phreg) ff <- function(formula,data,...) { ss <- survfit(formula,data,...) kmplot(ss,...) return(ss) } if (interactive()) { dcut(dat) <- ~"*.width" y <- S1~"*.4"|I(sepal.length>4) par(mfrow=c(1, 2)) xs <- dreg(dat, y, fun.=ff) }
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