View source: R/fixmodel_lin_cont.R
| fixmodel_lin_cont | R Documentation | 
This function performs linear regression taking into account all trial data until the arm under study leaves the trial and adjusting for time as a continuous covariate
fixmodel_lin_cont(data, arm, alpha = 0.025, ncc = TRUE, check = TRUE, ...)
data | 
 Data frame with trial data, e.g. result from the   | 
arm | 
 Integer. Index of the treatment arm under study to perform inference on (vector of length 1). This arm is compared to the control group.  | 
alpha | 
 Double. Significance level (one-sided). Default=0.025.  | 
ncc | 
 Logical. Indicates whether to include non-concurrent data into the analysis. Default=TRUE.  | 
check | 
 Logical. Indicates whether the input parameters should be checked by the function. Default=TRUE, unless the function is called by a simulation function, where the default is FALSE.  | 
... | 
 Further arguments passed by wrapper functions when running simulations.  | 
List containing the following elements regarding the results of comparing arm to control:
p-val - p-value (one-sided)
treat_effect - estimated treatment effect in terms of the difference in means
lower_ci - lower limit of the (1-2*alpha)*100% confidence interval
upper_ci - upper limit of the (1-2*alpha)*100% confidence interval
reject_h0 - indicator of whether the null hypothesis was rejected or not (p_val < alpha)
model - fitted model
Pavla Krotka
On model-based time trend adjustments in platform trials with non-concurrent controls. Bofill Roig, M., Krotka, P., et al. BMC Medical Research Methodology 22.1 (2022): 1-16.
trial_data <- datasim_cont(num_arms = 3, n_arm = 100, d = c(0, 100, 250),
theta = rep(0.25, 3), lambda = rep(0.15, 4), sigma = 1, trend = "linear")
fixmodel_lin_cont(data = trial_data, arm = 3)
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