vandenman / dstarm Goto Github PK

# data simulation
tt = seq(0, 5, .1)
pars = c(.8, 2, .5, .5, .5, # condition 1
         .8, 3, .5, .5, .5) # condition 2
pdfND = dbeta(tt, 10, 30)
lst = simData(n = 3e3, pars = pars, tt = tt, pdfND = pdfND, return.pdf = TRUE)
dat = lst$dat


# define restriction matrix
restr = matrix(1:5, 5, 2)
restr[2, 1:2] = 6:7 # allow drift rates to differ
# fix variance parameters
fixed = matrix(c('sz1', .5, 'sv1', .5), 2, 2)
#fit model
resD = estDstarM(dat = dat, tt = tt, restr = restr, fixed = fixed)
resND = estND(resD)
#estimate observed
resObs = estObserved(resD, resND)

# If the dataframe is properly sorted, no issue.
plotObserved(resObserved = resObs, data = dat,
             xlim = c(0, 1))
with(dat, table(condition, response)) 
#lower.1 = 267. OK!
#Not a problem there

#Flip data frame and re-run the analysis
dat = dat[nrow(dat):1, ]
head(dat)
resD = estDstarM(dat = dat, tt = tt, restr = restr, fixed = fixed)
resND = estND(resD)
resObs = estObserved(resD, resND)

#If the dataframe is not properly sorted, the issue arises
plotObserved(resObserved = resObs, data = dat,
             xlim = c(0, 1))
with(dat, table(condition, response)) 
#lower.1 = 1355. Not OK!
#Labels are switched.

fit2<-estDstarM(formula = is_pull ~ decisiongrab + is_target * is_spidertask, 
               data=ds, tt=(0:100)/100, verbose = T)

Error in getData(formula, data, verbose = verbose) : 
  More than 3 columns remained after specifying model.frame(formula, data = data)