سنجش

سنجش و اندازه گیری در علوم رفتاری

سنجش

سنجش و اندازه گیری در علوم رفتاری

مقایسه نرم افزار بایلوگ با وین استپز


Notes

Bilog

Winsteps

 

It is said that Rasch modeling is not the same as 1P modeling in Bilog.

Rasch is a philosophy of psychometrics, in which data fits the model, not the model fits the data

One-, two-, and three parameter models

Rasch model

Modeling

You can enter scaling options in Winsteps and Bilog.

Default: Probits

This is a escaling by 1.7

Default: Logits

Scale unit

Winsteps makes no assumptions about parameter distributions.

Bilog assumes normal sample distribution. This may squeeze or spread results particularly at the tails.

Normal sample distribution

No assumption

Assumptions

MMLE assumes the conditional independence of responses to different items by persons of the

same ability.

UCON is more biased than conditional methods, but this bias is negligibly small and always less than the standard errors of the estimated measures.

This usually has only decimal  place effects.

Marginal Maximum

Likelihood Estimate as the default.

MMAP and Bayes are also available

Joint Maximum Likelihood Estimate, also known as Unconditional Maximum Likelihood estimate (UCON).

Estimation

 

Person mean=0

Person variance=1

Item mean=0

Setting of origin

 

Multiple-form equating by using common or linking items

Across-sample test equating by using anchored items

Test equating

The numbers in the step function output are difficulty indices in terms of logit, the natural log of the odds ratio. Going from one point to two points, and from two points to three points, will certainly increase the logit difficulty.

Distances in logit are comparable. To be specific, if step3 - step2 = 0.1 and step2 - step1 = 0.1. The

two "0.1" are considered the same quantities.

Can handle  binary responses only

Can handle both dichotomous and partial credit items, use step functions

Partial credit

 

Fit statistic is expressed as Chi-square/degree of freedom, where Chi-square results are testing the fit between the expected and the observed.

Winsteps has two types of fitness  indexes: INMSQ (Infit mean square) and OUTSQ (Outfit mean square). The INMSQ is usually more informative than the OUTSQ.

Fitness

 

منبع:

Yu, Chong Ho & Sharon E. Osborn Popp (2005). Test Equating by Common Items and Common Subjects: Concepts and Applications. Practical Assessment Research & Evaluation, 10(4). Available online: http://pareonline.net/getvn.asp?v=10&n=4