atsmeans: Identify adaptive treatment strategy and estimate strategy...

In SMARTAR: Sequential Multiple Assignment Randomized Trial and Adaptive Randomization

Description

Return a message that lists all the adaptive treatment strategy embedded in SMART design. It also gives the estiamted strategy values and the variance-covariance matrix of estimated values.

Usage

atsmeans(
  data,
  family = c("gaussian", "binomial")[1],
  method = c("Gest", "IPW")[1],
  digits = NULL,
  common = FALSE,
  conf = TRUE,
  alpha = 0.05,
  plot = FALSE,
  title = "Strategy values with confidence interval",
  color = "forestgreen",
  ylab = "Strategy value",
  xlab = NULL,
  xtext = NULL,
  pch = 15,
  cex = 2,
  lwd = 3,
  ylim = NULL,
  mar = NULL,
  cex.axis = 1,
  line = NULL
)

Arguments

data	Input data frame of the sequential randomized trial (SMART) data used for analysis. The data should include the variables of stage-specific treatments (At; t=1,2,3), intermediate evaluation (Ot; t=1,2,3) and final primary outcome (Y), where t represent the number of stages embedded in design. If stage-1 treatment (A1) takes into account the information of baseline evaluation, O1 needed to be include in data, otherwise not.
family	A character string to specify the type of final primary outcome. The default is family=“gaussian”, which refers to the continuous primary outcome. If family=”binomial” then the primary outcome will be treated as binary variable.
method	A character string to specify the method of estimation. If method="Gest" then G-computation method is used. If method="IPW" then Inversed Probability Weighting method is used.
digits	An integer indicating the number of decimal places for sequence-specific mean and variance. Default is digits=NULL.
common	If common=TRUE, the pooled variance across all the treatment sequences are used in estimation. Otherwise use the sequence-specific variance. The default is common=FALSE.
conf	If conf=TRUE, output confidence intervals for estimate strategy values. The default is conf=TRUE.
alpha	Type I error rate control for confidence interval. The default is alpha=0.05.
plot	If plot=TRUE, output the graphs of treatment effects with CIs. The default is plot=TRUE.
title	Characters indicating the title of the graphs. Default is “Strategy values with confidence intervals”.
color	Characters indicating the color of the graphs. Default is color=“forestgreen”.
ylab	Characters to specify the label of the vertical axis of the output figure. Default is “Strategy value”.
xlab	characters to specify the label of the horizontal axis of the output figure.
xtext	Specification for the text of the horizontal axis of the graphs.
pch	An integer to specify the shape of points in the graphs. The default is pch=15.
cex	An integer to specify the amount by which plotting symbols should be magnified. The default is cex=2.
lwd	An integer to specify the line width, The lines refer to the width of the confidence interval. The default is lwd=1.
ylim	Integers to specify the maximum and minimum value of y axis.
mar	A numerical vector of the form c(bottom, left, top, right) which gives the number of lines of margin to be specified on the four sides of the plot.
cex.axis	The magnification to be used for the horizontal axis annotation relative to the current setting of cex.
line	Specifying a value for line overrides the default placement of label of the horizontal axis of the graphs.

Value

An object of “value” is return, which contain the index of all the adaptive treatment strategies, strategy-specific sample sizes and estimated values with standardized errors.

• ATS: Index of adaptive treatment strategy from 1 to G, where G is total number of strategies defined in SMART

• ds: Stage-specific decision makings given certain histories corresponding to each strategy. The number of columns of “ds” is defined by strategy and details are shown in the output.

• N: Number of subjects following a strategy.

• value: Estimated strategy values.

• se: standard errors of estimation

• lower.CI: Lower bound of (1-alpha) level confidence interval for strategy values

• upper.CI: Upper bound of (1-alpha) level confidence interval for strategy values

An object of “vmat” is return, which is variance-covariance matrix of estimated strategy values

References

Lavori P.W. and Dawson R. (2007). Improving the efficiency of estimation in randomization trials of adaptive treatment strategies. Clinical Trials, 4: 297-308.

Ko and Wahed A.S. (2015). Design of sequentially randomization trials for testing adaptive treatment strategies. Statistics in Medicine, 31, 812-830.

Examples

atsmeans(data=codiacs,family="gaussian",method="Gest",
conf=TRUE,common=TRUE,alpha=0.05,plot=TRUE,pch=12,lwd=2)

SMARTAR documentation built on July 31, 2020, 1:06 a.m.