stsubpop-class | R Documentation |

`"stsubpop"`

This is the S4 class for stepp subpopulation object. The subpopulations are generated based on the stepp windows and the covariate of interest.

Objects can be created by calls of the form `new("stsubpop")`

or the constructor method stepp.subpop.

`win`

:Object of class

`"stwin"`

the stepp window set up for the analysis`covar`

:Object of class

`"numeric"`

the covariate of interest`nsubpop`

:Object of class

`"numeric"`

the number of subpopulations generated`subpop`

:Object of class

`"ANY"`

a matrix of subpopulations generated based on the stepp window and the specified covariate of interest`npatsub`

:Object of class

`"numeric"`

a vector of size of each subpopulation`medianz`

:Object of class

`"numeric"`

a vector of median value of the covariate of interest for each subpopulation`minc`

:Object of class

`"numeric"`

a vector of the minimum value of the covariate of interest for each subpopulation`maxc`

:Object of class

`"numeric"`

a vector of the maximum value of the covariate of interest for each subpopulation`neventsubTrt0`

:Object of class

`"numeric"`

or`NULL`

a vector containing the number of events in each subpopulation for the baseline treatment group`neventsubTrt1`

:Object of class

`"numeric"`

or`NULL`

a vector containing the number of events in each subpopulation for the active treatment group`init`

:Object of class

`"logical"`

a logical value indicating if the subpopulations have already been generated or not

- generate
`signature(.Object = "stsubpop", win, covariate, coltype, coltrt, trts, minsubpops)`

:

a method to generate the subpopulations based on the stepp window object and the specified covariate of interest. For event-based windows, also the event type (`coltype`

), treatment indicator (`coltrt`

), treatments list (`trts`

) and minimum number of subpopulations (`minsubpops`

) must be provided- summary
`signature(.Object = "stsubpop")`

:

a method to display the summary of the subpopulations generated

Wai-Ki Yip

`stwin`

, `stmodelKM`

,
`stmodelCI`

, `stmodelGLM`

,
`steppes`

, `stmodel`

,
`stepp.win`

, `stepp.subpop`

, `stepp.KM`

,
`stepp.CI`

, `stepp.GLM`

,
`stepp.test`

, `estimate`

, `generate`

```
showClass("stsubpop")
# create a steppp window
win1 <- stepp.win(type="sliding", r1=5,r2=10)
# generate the covariate of interest
Y <- rnorm(100)
# create and generate the stepp subpopulation
sp <- new("stsubpop")
sp <- generate(sp, win=win1, cov=Y)
summary(sp)
# event-based windows using the BIG data set
data(bigKM)
rxgroup <- bigKM$trt
time <- bigKM$time
evt <- bigKM$event
cov <- bigKM$ki67
swin_e <- new("stwin", type = "sliding_events", e1 = 10, e2 = 20)
subp_e <- new("stsubpop")
subp_e <- generate(subp_e, win = swin_e, covariate = cov, coltype = evt,
coltrt = rxgroup, trts = c(1, 2), minsubpops = 5)
summary(subp_e)
```

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