Showing papers on "Differential item functioning published in 1974"
TL;DR: In this paper, the authors derived a graphical approximation of the item parameters of the stochastic mental test models, i.e., the generalized normal ogive and logistic models.
Abstract: Equations were derived to enable the graphic approximation of the item parameters of the stochastic mental test models, i.e., the generalized normal ogive and logistic models. The item parameters for the models are discriminatory power (ai), difficulty (bi), and lower asymptote of the item characteristic curve (ci) where the item characteristic curve (ICC) is the regression of the binary item on latent ability. In brief, c i can be approximated through visual inspection of the left-hand (lower) asymptote of the proportion passing the item plotted against the total test score minus the particular item. Thereafter, a graph appropriate to the approximate ci can be consulted to convert an ordinary item-total test point-biserial correlation and proportion passing the item into approximations of item discriminatory power (ai) and item difficulty (bi). Suggested uses for the approximations were to provide a basis for screening items for tailored testing, to enable a determination as to the appropriateness of a s...
46 citations
TL;DR: The process culminating in the response to an item in a personality inventory affects the value of that response's contribution to test score as discussed by the authors, and some response components are inappropriate from the ex...
Abstract: The process culminating in the response to an item in a personality inventory affects the value of that response's contribution to test score. Some response components are inappropriate from the ex...
26 citations
TL;DR: In this article, it has been argued that item variance and test variance are not necessary characteristics for criterion-referenced tests, although they are necessary for norm-based tests.
Abstract: It has been argued that item variance and test variance are not necessary characteristics for criterion-referenced tests, although they are necessary for normreferenced tests. This position is in error because it considers sample statistics as the criteria for evaluating items and tests. Within a particular sample, an item or test may have no variance, but in the population of observations for which the test was designed, calibrated, and evaluated, both items and tests must have variance.
21 citations
TL;DR: In this article, the authors considered a logistic model for item analysis where the probability of a subject solving an item in a test is given by the probability δζ/(1 + δ ζ).
Abstract: Rasch [4] considered a logistic model for item analysis where the probability of a subject solving an item in a test is given by the probability δζ/(1 + δζ). where δ characterizes the ability of the person and ζ characterizes the easiness of the item. The same model was used by Sanathanan [6] in a visual scanning set up where a “scanner” takes the role of an “item” and an “event” that of a “subject.” In the visual scanning model it is further assumed that the event parameter is a random variable. Some properties of the logistic model in relation to both the item analysis and scanning problems are studied here.
5 citations