Description Usage Arguments Value References Examples
View source: R/CalculateSampleSize.R
This function calculates the sample size for microrandomized trials (MRTs) based on methodology developed in Sample Size Calculations for Microrandomized Trials in mHealth by Liao et al. (2016) <DOI:10.1002/sim.6847>.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16  calculateSampleSize(
days,
occ_per_day,
prob,
beta_shape,
beta_mean,
beta_initial,
beta_quadratic_max,
tau_shape,
tau_mean,
tau_initial,
tau_quadratic_max,
dimB,
power,
sigLev
)

days 
The duration of the study. 
occ_per_day 
The number of decision time points per day. 
prob 
The randomization probability, i.e. the probability of assigning the treatment at a decision time point. This can be constant, or timevarying probabilities can be specified by by a vector specifying randomization probabilities for each day or decision time. 
beta_shape 
The trend for the proximal treatment effect; choices are constant, linear or quadratic. Note:

beta_mean 
The average of proximal treatment effect. 
beta_initial 
The initial value of proximal treatment effect when beta_shape is linear or quadratic. 
beta_quadratic_max 
Day of maximal proximal treatment effect when beta_shape is quadratic. 
tau_shape 
The pattern for expected availability; choices are constant, linear or quadratic. Note:

tau_mean 
The average of expected availability. 
tau_initial 
The initial Value of expected availability when tau_shape is linear or quadratic. 
tau_quadratic_max 
The changing point of availability when tau_shape is quadratic. 
dimB 
The number of parameters used in the main/average effect of proximal outcome. 
power 
The desired power to achieve. 
sigLev 
The significance level or type I error rate. 
The minimal sample size to achieve the desired power.
Seewald, N.J.; Sun, J.; Liao, P. "MRTSS Calculator: An R Shiny Application for Sample Size Calculation in MicroRandomized Trials". arXiv:1609.00695
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30  calculateSampleSize(days=42,
occ_per_day=5,
prob=0.4,
beta_shape="quadratic",
beta_mean=0.1,
beta_initial=0,
beta_quadratic_max=28,
tau_shape="quadratic",
tau_mean=0.5,
tau_initial=0.7,
tau_quadratic_max=42,
dimB=3,
power=0.8,
sigLev=0.05)
prob1 < c(replicate(35,0.7),replicate(35,0.6),replicate(35,0.5),replicate(35,0.4))
calculateSampleSize(days=28,
occ_per_day=5,
prob=prob1,
beta_shape="quadratic",
beta_mean=0.1,
beta_initial=0,
beta_quadratic_max=28,
tau_shape="quadratic",
tau_mean=0.5,
tau_initial=0.7,
tau_quadratic_max=42,
dimB=3,
power=0.8,
sigLev=0.05)

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