gsearly (version 1.0.0)

modelParameters: Estimates model parameters from raw data

Description

Provides estimates of the variance of beta (vbeta) and beta, the treatment effect, directly from raw data and a user supplied covariance matrix.

Usage

modelParameters(data, datanames=c("id", "atime", "intervention", "outcome"),
              vcovmat)

Value

Returns the variance of beta (vbeta), beta and test statistic z.

Arguments

data

A data frame structured as those from function simdataExtract, with full=TRUE, but without the requirement for a standardized (continuous) time-point (see tfuStandard).

datanames

Names of the four variables in the data frame data that are respectively participant id, time-point, intervention arm and outcome, in that order.

vcovmat

A covariance matrix of dimensions s x s.

See Also

gsearlySimulate, simdataExtract

Examples

 # For 90 percent power (pow), a call to gsearlyModel provides a feasible design
 fp <- c(0.0000,0.0010,0.0250)
 tn <- c(0.2400,0.7200,0.9750)
 modeldesign <- gsearlyModel(rmodel="dilin", trecruit=36, s=3, tfu=c(3,6,12),
                   tinterims=c(18,30), pow=0.9, vphi=0.5, m=2,
                   cmodel="uniform", sd=20, rho=0.5, theta=8, fp=fp, tn=tn)

 # Simulate data from this model with raw data using full=TRUE
 simdata <- gsearlySimulate(mod=modeldesign, nsim=10, full=TRUE)

 # Extract raw data for a single simulation
 simdat1 <- simdataExtract(simdata, simn=1, tinterims=18, full=TRUE)
 # Get model parameters
 modelParameters(data=simdat1$data, vcovmat=simdat1$model$covariance)

 # Try alternative covariance model
 varmat <- diag(c(18,22,24))
 vcovmat <- tcrossprod(crossprod(varmat,corrExp(rho=0.8,
                                            tfu=simdat1$model$tfu)),varmat)
 modelParameters(data=simdat1$data, vcovmat=vcovmat)