a1Table {adaptTest}

Function to produce tables of alpha1

Description

This function produces tables of \alpha_1 for a grid of different choices of \alpha and \alpha_0.

Usage

a1Table(typ, a = NA, a0 = NA, Pocock = FALSE, round = FALSE)

Arguments

typ

type of test: "b" for Bauer and Koehne (1994), "l" for Lehmacher and Wassmer (1999), "v" for Vandemeulebroecke (2006) and "h" for the horizontal conditional error function

a

vector of different choices of \alpha, the overall test level

a0

vector of different choices of \alpha_0, the futility stopping bound

Pocock

logical determining whether the "Pocock-type" should be calculated or the full level should be applied after the second stage (see details; default: full level after second stage).

round

rounding specification, logical or integer (see details; default: no rounding)

Details

This function produces tables of \alpha_1 on a grid spanned by the vectors a and a0 (i.e., \alpha and \alpha_0). This is done either for the "Pocock-type" (i.e., under the condition \alpha_1 = \alpha_2: Pocock = TRUE) or using the full level after the second stage (\alpha = \alpha_2: Pocock = FALSE (the default)). The function a1Table can be a convenient shortcut for a repeated use of tsT; see this latter function for further details.

The result is rounded to round digits after the comma (round = TRUE rounds to 1 digit; round = FALSE and round = 0 prevent rounding).

Value

a1Table returns a matrix of \alpha_1 values, with the corresponding \alpha and \alpha_0 values being displayed as dimnames.

Author(s)

Marc Vandemeulebroecke

References

Bauer, P., Koehne, K. (1994). Evaluation of experiments with adaptive interim analyses. Biometrics 50, 1029-1041.

Lehmacher, W., Wassmer, G. (1999). Adaptive sample size calculations in group sequential trials. Biometrics 55, 1286-1290.

Vandemeulebroecke, M. (2006). An investigation of two-stage tests. Statistica Sinica 16, 933-951.

See Also

adaptTest package description, tsT

Examples

## Produce basic reference tables for the test by Vandemeulebroecke (2006)
alpha  <- c(0.1, 0.05, 0.025, 0.01)
alpha0 <- 1:10/10
a1Table(typ="v", a=alpha, a0=alpha0, Pocock=FALSE)
a1Table(typ="v", a=alpha, a0=alpha0, Pocock=TRUE)