REMB-class: An S4 class to represent the results using the random effect...
In dfmeta: Meta-Analysis of Phase I Dose-Finding Early Clinical Trials
Description
An S4 class to represent the results using the random effect model-based (REMB) algorithm.
Slots
dataToxA data frame containing information for each patient at each simulation and trial.
sim0The simulation starting point; must be numeric.
sim1The simulation ending point; must be numeric.
familyA distribution family for the response variable; defaults to binomial distribution. See glm and glmer for details.
linkA specification for the model link function. This can be a name/expression, a literal character string or a length-one character vector; defaults to logit link function. See glmer for details.
estimatesA data frame including the predicted toxicity probabilities (column named as "rndpt") using either the predicted random effect center "mu" (column named as "PredMu"), if it's available, or the value ratio (i.e. # of toxicities / # of subjects) if the corresponding "mu" is not available. Note that, "PredMu" value is equal to "NA" when there is no prediction for it.
dfmeta documentation built on May 1, 2019, 7:59 p.m.
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Description
An S4 class to represent the results using the random effect model-based (REMB) algorithm.
Slots
dataToxA data frame containing information for each patient at each simulation and trial.
sim0The simulation starting point; must be numeric.
sim1The simulation ending point; must be numeric.
familyA distribution family for the response variable; defaults to binomial distribution. See
glmandglmerfor details.linkA specification for the model link function. This can be a name/expression, a literal character string or a length-one character vector; defaults to logit link function. See
glmerfor details.estimatesA data frame including the predicted toxicity probabilities (column named as "rndpt") using either the predicted random effect center "mu" (column named as "PredMu"), if it's available, or the value ratio (i.e. # of toxicities / # of subjects) if the corresponding "mu" is not available. Note that, "PredMu" value is equal to "NA" when there is no prediction for it.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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