lmmModel_estimates {SynergyLMM} | R Documentation |
Get estimates from a linear mixed model of tumor growth data
Description
lmmModel_estimates
allows the user to easily extract some of the interesting model estimates for further use in other functions,
such as for power calculation.
Usage
lmmModel_estimates(model)
Arguments
model |
An object of class "lme" representing the linear mixed-effects model fitted by |
Details
The model estimates provided by lmmModel_estimates
include:
Fixed effect coefficients:
\hat{\beta}_C
,\hat{\beta}_A
,\hat{\beta}_B
,\hat{\beta}_{AB}
, which represent the estimated specific growth rates for the Control, Drug A, Drug B and Combination groups, respectively. These are shown in columnscontrol
,drug_a
,drug_b
, andcombination
, respectively.Standard deviation of the random effects (between-subject variance). Column
sd_ranef
.Standard deviation of the residuals (within-subject variance). Column
sd_resid
.
Value
A data frame with the estimated values for the coefficients of the tumor growth for each treatment,
the standard deviation of the random effects, and the standard deviation of the residuals of the model.
These values can be useful for the power analysis of the model using APrioriPwr()
.
Examples
data("grwth_data")
# Fit example model
lmm <- lmmModel(
data = grwth_data,
sample_id = "subject",
time = "Time",
treatment = "Treatment",
tumor_vol = "TumorVolume",
trt_control = "Control",
drug_a = "DrugA",
drug_b = "DrugB",
combination = "Combination"
)
# Get the estimates
lmmModel_estimates(lmm)