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MAPpriorNew_cont()
Analysis for continuous data using the MAP Prior approach
MAPprior_bin()
Analysis for binary data using the MAP Prior approach
MAPprior_cont()
Analysis for continuous data using the MAP Prior approach
datasim_bin()
Simulate binary data from a platform trial with a shared control arm and a given number of experimental treatment arms entering at given time points
datasim_cont()
Simulate continuous data from a platform trial with a shared control arm and a given number of experimental treatment arms entering at given time points
fixmodel_bin()
Frequentist logistic regression model analysis for binary data adjusting for periods
fixmodel_cal_bin()
Frequentist logistic regression model analysis for binary data adjusting for calendar time units
fixmodel_cal_cont()
Frequentist linear regression model analysis for continuous data adjusting for calendar time units
fixmodel_cont()
Frequentist linear regression model analysis for continuous data adjusting for periods
gam_cont()
Generalized additive model analysis for continuous data
get_ss_matrix()
Sample size matrix for a platform trial with a given number of treatment arms
inv_u_trend()
Generation of an inverted-u trend
linear_trend()
Generation of a linear trend that starts in a given period
mixmodel_AR1_cal_cont()
Mixed regression model analysis for continuous data adjusting for calendar time units as a random factor with AR1 correlation structure
mixmodel_AR1_cont()
Mixed regression model analysis for continuous data adjusting for periods as a random factor with AR1 correlation structure
mixmodel_cal_cont()
Mixed regression model analysis for continuous data adjusting for calendar time units as a random factor
mixmodel_cont()
Mixed regression model analysis for continuous data adjusting for periods as a random factor
mixmodel_int_cal_cont()
Mixed regression model analysis for continuous data using the covariates treatment and calendar time unit as fixed effects and the interaction between them as a random effect
mixmodel_int_cont()
Mixed regression model analysis for continuous data using the covariates treatment and period as fixed effects and the interaction between them as a random effect
piecewise_cal_cont()
Model-based analysis for continuous data using discontinuous piecewise polynomials per calendar time unit
piecewise_cont()
Model-based analysis for continuous data using discontinuous piecewise polynomials per period
plot_trial()
Function for visualizing the simulated trial
poolmodel_bin()
Pooled analysis for binary data
poolmodel_cont()
Pooled analysis for continuous data
seasonal_trend()
Generation of a seasonal trend
sepmodel_adj_bin()
Separate analysis for binary data adjusted for periods
sepmodel_adj_cont()
Separate analysis for continuous data adjusted for periods
sepmodel_bin()
Separate analysis for binary data
sepmodel_cont()
Separate analysis for continuous data
sim_study()
Wrapper function performing simulation studies for a given set of scenarios (not parallelized)
sim_study_par()
Wrapper function performing simulation studies for a given set of scenarios (parallelized on replication level)
splines_cal_cont()
Spline regression analysis for continuous data with knots placed according to calendar time units
splines_cont()
Spline regression analysis for continuous data with knots placed according to periods
sw_trend()
Generation of stepwise trend with equal jumps between periods
timemachine_bin()
Time machine analysis for binary data
timemachine_cont()
Time machine analysis for continuous data
datasim_bin_2()
Simulate binary data from a platform trial with a shared control arm and a given number of experimental treatment arms entering at given time points using a user-specified sample size matrix
fixmodel_lin_cont()
Frequentist linear regression model analysis for continuous data with linear adjustment for time
powerprior_cont()
Analysis for continuous data using the power prior approach