emaxPrior.control {clinDR} | R Documentation |
Set the parameters of the prior distribution for the Emax model implemented in fitEmaxB
.
Description
Set the parameters of the prior distribution for the Emax model implemented in fitEmaxB.
.
Usage
emaxPrior.control(epmu=NULL,epsca=NULL,
difTargetmu=NULL,difTargetsca=NULL,
dTarget=NULL,p50=NULL,
sigmalow=NULL,sigmaup=NULL,
effDF=parmDF,parmDF=5,
loged50mu=0.0,loged50sca=1.73,
loglammu=0.0,loglamsca=0.425,parmCor=-0.45,
lowled50=log(0.001),highled50=log(1000),
lowllam=log(0.3),highllam=log(4.0),
basemu=NULL,basevar=NULL,binary=FALSE)
Arguments
epmu |
Mean for |
epsca |
The scale parameter for |
difTargetmu |
Mean for the prior distribution of the effect at dose |
difTargetsca |
The scale parameter for the prior distribution of the effect at dose |
dTarget |
Target dose for prior effect. Typically the highest dose planned and/or the proof-of-concept dose. |
p50 |
Projected |
sigmalow |
Lower bound for a uniform prior distribution for the residual SD (continuous data). |
sigmaup |
Upper bound for a uniform prior distribution for the residual SD (continuous data). |
effDF |
The degrees of freedom for the prior distributions for the |
parmDF |
The degrees of freedom of the bivariate log-t prior distribution for the |
loged50mu |
Mean of prior t-distribution for the |
loged50sca |
Scale (analogous to SD) of the prior t-distribution for the |
loglammu |
Mean of prior t-distribution for the Hill parameter lambda. See references for its default value and interpretation. |
loglamsca |
Scale (analogous to SD) of the prior t-distribution for the Hill parameter lambda. |
parmCor |
Correlation for the bivariate log-t prior distribution for the |
lowled50 , highled50 , lowllam , highllam |
Bounds applied to the prior distributions for the log(ED50/P50) and log(lambda). The original (unbounded) priors are modified to be conditional on being within the bounds. This is done for numerical stability and plausibility of the parameter values |
basemu |
A vector of prior means for the covariate regression parameters. |
basevar |
The prior variance-covariance matrix for the covariate regression parameters. The covariate regression parameters are a priori independent of the other dose response model parameters. |
binary |
Set to |
Details
The prior distribution is based on meta-analyses of dose response described in the references. The E0 and difTarget parameters have independent t-distribution prior distributions. For binary data, these parameters are computed on the logistic scale. The prior means and scales of these parameters must be assigned compound-specific values. The predicted ED50 at the study design stage must must also be specified as 'P50'. For continuous data, the prior distribution for the residual SD is uniform on a user-specifed scale.
The prior distribution of the log(ED50) has a t-distribution
centered at log(P50), with scale, degrees of freedom (parmDF),
and offset to the P50,
defaulting to values given in the references (these can be changed, but they
are difficult to interpret outside the context of the meta-analyses).
If modType=4
, the prior distribution for the Hill parameter
is also t-distribution with parmDF degrees of freedom and corParm
correlation with the log(ED50).
Value
List of class emaxPrior
of prior parameter values for use in
fitEmaxB
. default
is a derived variable set to
TRUE
when the default values are used for loged50
and loglambda
.
Author(s)
Neal Thomas
References
Thomas, N., Sweeney, K., and Somayaji, V. (2014). Meta-analysis of clinical dose response in a large drug development portfolio, Statistics in Biopharmaceutical Research, Vol. 6, No.4, 302-317. <doi:10.1080/19466315.2014.924876>
Thomas, N., and Roy, D. (2016). Analysis of clinical dose-response in small-molecule drug development: 2009-2014. Statistics in Biopharmaceutical Research, Vol. 6, No.4, 302-317 <doi:10.1080/19466315.2016.1256229>
Wu, J., Banerjee, A., Jin, B., Menon, S., Martin, S., and Heatherington, A. (2017). Clinical dose-response for a broad set of biological products: A model-based meta-analysis. Vol. 9, 2694-2721. <doi:10.1177/0962280216684528?>
See Also
fitEmaxB