This is the development version of the DstarM package.
vandenman / dstarm Goto Github PK
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R package DstarM
When I run the following code,
fit2<-estDstarM(formula = is_pull ~ decisiongrab + is_target * is_spidertask,
data=ds, tt=(0:100)/100, verbose = T)
I get this error:
Error in getData(formula, data, verbose = verbose) :
More than 3 columns remained after specifying model.frame(formula, data = data)
I had a look in the getData() function and it seems to simply check the number of terms on the right-hand side, and error if there are more than 3 of them (incl the reaction time term). However, this is inconsistent with the help file: there, it is suggested that you can specify as many conditions as you want.
Thanks for the package. I found a minor bug.
If the first response that appears in the dataframe used to fit a model is the second level of the response factor, then the labels in the qqplots produced by plotObserved are wrong. The same happens if the first condition that appears in the dataframe is not condition 1.
I could circumvent this issue by sorting the data beforehand (e.g. dat <- dat[order(dat$response, dat$condition), ]).
Here is some code that reproduces the issue.
# 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.
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