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# This wrapper will source the script "simulation script ABV method.R' to simulate data for r runs of j studies of i participants.# 
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#set number of simulation runs 'r':
nr = 10

#set number of studies 'j' in each run 'r':
nj = 1000

#set number of participants 'ni_GrpB' and 'ni_GrpB' for each subset 'A' and 'B' for all simulated studies  
ni_GrpA = 26
ni_GrpB = 26

# set number of trials 
nCT = 64
nIT = 64
nNT = 32

# NB! for the ABV script, the number of CT and IT trials MUST be twice the number of NT trials!! 

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#                                      Parameters for drawing random data ("response times")                                       # 
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#### set the initial parameters for RT mean and standard deviation ####
# These are the parameters used for all studies ('j')in the first run ('r'). 
# For groups a A these parameters will be modified as specified below from the second run onwards
# For groups B these parameters are retained over each run - except when dynamic is set to 1 or 2 (see below). 

# set start parameters for both groups:
start_mean <- 600
start_SD <- 30
  
# set parameters to change over runs 'r':
SD_increase = 2  # at the start of each run increase SD rt for both IT & CT trials in groups A (groups B remain at start_SD)
                 # (0 = keep constant, 2 = +2 ms in run 2, +4 ms in run 3, etc.)

Mn_increase = 0  # at the start of each run increase the mean rt for both IT & CT trials in groups A (groups B remain at start_mean)
                 # (0 = keep constant, 20 = +20 ms in run 2, +40 ms in run 3, etc.)

BI_increase = 0  # at the start of each run increase bias in groups A - half this value will be subtracted from the mean CT value, half this value added to the mean IT value.
                 # (0 = keep constant, 3 = create a difference of 3 ms in run 2, a difference of 6 ms in run 3, etc.)

dynamic = 0      # 0: no dynamic; 
                 # 1: increase frequency of switches over runs (every 1/r *total number of trials) in group A,
                 #     no increases in SD, mean or BI will be applied (!). 
                 #     in group B the fixed bias is kept constant (at value fixed_BI) within each data set (no switches) and over runs. 
                 # 2: increase BI amplitude in groups A using value given for BI_increase and also 
                 #     implement N_swithces number of switches and a 'fixed_BI'-sized bias in both groups.

fixed_BI = 0     # value for fixed_BI to use when dynamic is either 1 or 2

Nswitches = 0    # number of switches to implement when dynamic = 2



#run simulation with above entered parameters:
source("simulation script ABV method.R")


# save output:
SaveSimOutput(method= "TLBS", CSV= FALSE, RDS=TRUE, docx=TRUE)


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