itemListToThresholds {conquestr}  R Documentation 
Taskes a list of item parameter matricies and returns a data frame containing Thurstonian Thresholds (gammas) for all items. Thurstonian thresholds are the location on the trait/scale at which the cumulative probability of being in category k, or any higher category equals some probability (usually 0.5, the default). Thurstonian thresholds are considered a way of describing the difficulty of polytomously scored items and are usually the value used in visualisations like Wright maps. Thurstonian thresholds can only be calculated for items where response categories are scored such that each category can be placed in an order increasing scores (e.g., no ties as per the Ordered Partition model)
itemListToThresholds(
myItems,
threshP = 0.5,
minTheta = 20,
maxTheta = 20,
convC = 1e05
)
myItems 
A list of item parameter matricies of the structure used in 
threshP 
The probability at which the thresholds are calculated (defaults to the usual value of 0.5) 
minTheta 
The lowerbound starting value of the splithalf search used to find the threshold for the category. 
maxTheta 
The upperbound starting value of the splithalf search used to find the threshold for the category. 
convC 
The convergence criteria used to determine when the threshold has been found. The difference between

A data frame including 4 columns:
id, an integer index reflecting which item this is, in the same order as myItems
itemid, a string with the names from the items in myItems (NA if item list is not named)
step, which step does this threshold belong?
location, the value of the threshold
myItem < matrix(
c(
0, 0.58 , 0 , 1, # delta+tau thurst thresh (gamma)
1, 0.58 , 0.776 , 1, # 0.196 1.14
2, 0.58 , 0.697 , 1, # 1.277 0.93
3, 0.58 , 0.629 , 1, # 1.209 0.64
4, 0.58 , 0.55 , 1 # 0.03 0.25
), ncol =4, byrow=TRUE
)
itemListToThresholds(list(myItem))