stwin-class {stepp}

Class "stwin"

Description

This the S4 class for the stepp window object. The stepp window class describes the way to set up the subpopulation for a stepp analysis. It specifies a pattern of subpopulation you would like to explore. There are three kinds of patterns: "sliding window", "event-based sliding window" and "tail-oriented window".

These patterns are specified through the following set of values (r1 and r2 for sliding and tail-oriented windows, e1 and e2 for event-based sliding windows):

1. for sliding windows based on the number of patients ("sliding"), r1 is the minimum number of patients allowed in overlapping windows and r2 is the approximate size of subpopulation in each window;

2. for sliding windows based on the number of events ("sliding_events"), e1 is the minimum number of events allowed in overlapping windows and e2 is the approximate size of subpopulation in each window in terms of number of events;

3. for tail-oriented window, r1 is a vector of maximum covariate value for each subpopulation from the minimum value of the entire subpopulation, and r2 is a vector of minimum covariate values for each subpopulation from the maximum value of the window. The utility function gen.tailwin() can be used to generate these vectors based on the number of desired subpopulations.

When "sliding_events" is chosen r1 and r2 are set to NULL, while when "sliding" or "tail-oriented" are chosen e1 and e2 are set to NULL.

These pattern are based on all patients.

Objects from the Class

Objects can be created by calls of the form new("stwin", type="sliding", r1=5, r2=20) or the constructor function stepp.win.

Slots

type:

Object of class "character"
stepp window type; "sliding", "sliding_events" or "tail-oriented"

r1:

Object of class "numeric" or NULL
sliding window: minimum number of patients allowed in overlapping windows;
tail-oriented window: a vector of maximum covariate value for each subpopulation

r2:

Object of class "numeric" or NULL
sliding window: size of subpopulation in each window;
tail-oriented window: a vector of minimum covariate value for each subpopulation

e1:

Object of class "numeric" or NULL
event-based sliding window: minimum number of events allowed in overlapping windows

e2:

Object of class "numeric" or NULL
event-based sliding window: number of events in each subpopulation

Methods

summary

signature(object = "stwin"):
print a summary of the stepp windows object

Author(s)

Wai-Ki Yip

See Also

stsubpop, stmodelKM, stmodelCI, stmodelGLM, steppes, stmodel, stepp.win, stepp.subpop, stepp.KM, stepp.CI, stepp.GLM, stepp.test, estimate, generate

Examples

  showClass("stwin")

  # create a stepp window of type "sliding" with (r2) size of subpopulation
  # in each window to be 200 and (r1) allows only 50 patients in the
  # overlapping windows
  mywin <- new("stwin", type="sliding", r1=50, r2=200)

  # print a summary of the stepp window object created
  summary(mywin)

  # create a stepp window object of type "sliding_events", 
  # (event-based) subpopulation size is 200 and allows
  # only 50 events between overlapping windows
  mywin <- stepp.win(type="sliding_events", e1=50, e2=200)

  # print a summary of the stepp window object
  summary(mywin)