| emaxPrior.control | 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
parameters implemented in fitEmaxB..
Usage
emaxPrior.control(mixP=0,epmu=NULL,epsca=NULL,
mu_ep=NULL, sd_ep = NULL, w_ep=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
mixP |
The number of mixture components included in the prior distribution
of the placebo response ( |
mu_ep |
For the mixture prior prior, a numeric vector of component means. Each entry gives the mean of the normal distribution associated with that component. Logistic scale for binary data. |
sd_ep |
For the mixture prior prior, a numeric vector of component standard deviations. Each entry gives the standard deviation of the normal distribution associated with that component. Logistic scale for binary data. |
w_ep |
For the mixture prior prior, a numeric vector of mixture weights. Each weight specifies the relative contribution of the corresponding component to the overall distribution. |
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 the 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.
Covariate adjustment with a mixture PBO prior ( |
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.
Covariate adjustment with a mixture PBO prior ( |
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).
If mixP>0, any non null value specified under epmu
and epsca will be ignored.
The model will consider mixture normal distribution alone for E0 prior.
The t-distribution will be ignored.
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