Winsteps chooses the model-family based on MODELS=

Models=R (or MODELS= is omitted) is the rating-scale family of models which includes the Andrich Rating-Scale Model, the Masters Partial-Credit Model, the Grouped Rating-Scale Model and the Rasch Dichotomous Model.

 

 

Within Models=R, the choice of model is decided by ISGROUPS=

If ISGROUPS= is omitted, then

1) If there are only two categories in the data the dichotomous model

2) If there are more than two categories the Andrich Rating-Scale Model

 

If ISGROUPS=0 then

the Masters Partial Credit Model

 

If ISGROUPS=(something else)

the Grouped Rating-Scale Model

 

Please look at the output in Table 3.2, 3.3, .... to see exactly how the data have been modeled.

 

Winsteps estimates calibrations for four different ordered response category structures. Dichotomies are always analyzed using the Rasch dichotomous model, regardless of what model is specified for polytomies. Items are assigned to the model for which the serial location in the MODELS= string matches the item sequence number.

 

The item grouping default becomes the "Partial Credit Model' each item with its own rating scale: MODEL=R and ISGROUPS=0.

 

Do not specify MODELS= unless you intend to use the "S" or "F" models.

 

MODELS=R (standard) is the default option, specifying standard Rasch analyses using the Rasch dichotomous model, Andrich "Rating Scale" model and Masters' "Partial Credit" model, see ISGROUPS=.

Andrich D. (1978) A rating scale formulation for ordered response categories. Psychometrika, 43, 561-573.

Masters G.N. (1982) A Rasch model for partial credit scoring. Psychometrika, 47, 149-174.

 

MODELS=S uses the Rasch dichotomous model and the Glas-Verhelst "Success" (growth) model, also called the "Steps" Model (Verhelst, Glas, de Vries, 1997). If and only if the person succeeds on the first category, another category is offered until the person fails, or the categories are exhausted, e.g. an arithmetic item, on which a person is first rated on success on addition, then, if successful, on multiplication, then, if successful, on division etc. "Scaffolded" items can function this way. This is a continuation ratio model parameterized as a Rasch model with missing data on unreached categories. Verhelst N.D., Glas C.A.W. & De Vries H.H. (1997) A Steps model to analyze partial credit. In W.J. van der Linden & R.K. Hambleton (Eds.), Handbook of modern item response theory (pp. 123 - 138) New York: Springer.

Recommendation: Instead of an S-type polytomy, model each step to be a dichotomy: 1=succeeded, 0=failed, missing=not reached. This facilitates much more powerful diagnosis of the functioning of the success process.

 

MODELS=F uses the Rasch dichotomous model and the Linacre "Failure" (mastery) model. If a person succeeds on the first category, top rating is given and no further categories are offered. On failure, the next lower category is administered until success is achieved, or categories are exhausted. This is a continuation ratio model parameterized as a Rasch model with missing data on unreached categories. The Success and Failure model computations were revised at Winsteps version 3.36, August 2002.

Recommendation: Instead of an F-type polytomy, model each step to be a dichotomy: 1=succeeded, 0=failed, missing=not reached. This facilitates much more powerful diagnosis of the functioning of the failure process.

 

MODELS= has three forms: MODELS=RRSSFR and MODELS=* list * and MODELS=*filename. When only one letter is specified with MODELS=, e.g., MODELS=R, all items are analyzed using that model. Otherwise MODELS=some combination of R's, F's, S's, and G's, e.g., MODELS=RRSF

 

When XWIDE=2 or more, then

either (a) Use one character per XWIDE and blanks,

  NI=8

  XWIDE=2

  MODELS=' R S R F R S R R' ; this also forces ISGROUPS=0 to be the default

or (b) Use one character per item with no blanks

  NI=8

  XWIDE=2

  RESCORE='RSRFRSRR' ; this also forces ISGROUPS=0 to be the default

 

Example 1: All items are to be modeled with the "Success" model.

  MODELS=S ; the Success model

 

Example 2: A competency test consists of 3 success items followed by 2 failure items and then 10 dichotomies. The dichotomies are to be reported as one grouping.

  NI=15  fifteen items

  MODELS=SSSFFRRRRRRRRRR ; matching models: ; forces ISGROUPS=0 to be the default

  ISGROUPS=000001111111111 ; dichotomies grouped: overriding the default ISGROUPS=0 

or

  MODELS=*

  1-3 S

  4 F

  5 F

  6-15 R

  *