# List Experiment “ictreg.joint” error: “log-likelihood is not monotonically increasing”

I'm trying to use "ictreg.joint" function in "list" package in R by Imai and Blair to use the predicted responses from the list experiment as the explanatory variable to analyze an outcome variable. However, I get this error:

Error in if (llik.const < pllik.const) warning("log-likelihood is not monotonically increasing.") : missing value where TRUE/FALSE needed

I have tried dropping NAs, converting to tibble, etc but still get the error. I have checked the "class" of all the variables, and they are in the integers, the same class as the variables in the Mexico dataset Imai and Blair used (in "Examples" box in the ictreg.joint link above). In fact, I have also tried using other list experiment replication datasets, and got the same error. The only dataset that the function works with is the Mexico dataset.

I use a modification of their own code:

supportreg.uk <- ictreg.joint(formula = y ~  age + gender + socialgrade +
covidconcern +
conservative,
data = data,
treat = "treat",
outcome = "support",
J = 4,
constrained = TRUE,
outcome.reg = "linear",
maxIter = 100)


Has anyone used ictreg.joint before and/or have you encountered the error above? I am happy to provide a sample of the data, but I'd have to send it individually (original data, owned by the lab I work for).

Many thanks!

Reference

Imai, Kosuke, Bethany Park, and Kenneth F. Greene. (2014) $$$$Using the Predicted Responses from List Experiments as Explanatory Variables in Regression Models.'' available at http://imai.princeton.edu/research/files/listExp.pdf