fixmodel_cal_cont {NCC} | R Documentation |
Frequentist linear regression model analysis for continuous data adjusting for calendar time units
Description
This function performs linear regression taking into account all trial data until the arm under study leaves the trial and adjusting for calendar time units as factors.
Usage
fixmodel_cal_cont(
data,
arm,
alpha = 0.025,
unit_size = 25,
ncc = TRUE,
check = TRUE,
...
)
Arguments
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. |
unit_size |
Integer. Number of patients per calendar time unit. Default=25. |
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. |
Details
The model-based analysis adjusts for the time effect by including the factor calendar time unit (defined as time units of fixed length, defined by ùnit_size
). The time is then modelled as a step-function with jumps at the beginning of each calendar time unit.
Denoting by the continuous response for patient
, by
the arm patient
was allocated to, and by
the treatment arm under evaluation, the regression model is given by:
where is the response in the control arm in the first calendar time unit;
represents the effect of treatment
compared to control for
, where
is the set of treatments
that were active in the trial during calendar time units prior or up to the time when the investigated treatment arm left the trial;
indicates the stepwise calendar time effect between calendar time units 1 and
(
), where
denotes the calendar time unit, in which the investigated treatment arm left the trial.
If the data consists of only one calendar time unit, the calendar time unit in not used as covariate.
Value
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
Author(s)
Pavla Krotka
Examples
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_cal_cont(data = trial_data, arm = 3)