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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.