1998Unpublished venueOpen access

An Investigation of Factors Affecting Test Equating in Latent Trait Theory

Surintorn Suanthong

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Abstract

The study investigated five factors which can affect the equating of scores from two tests onto a common score scale. The five factors were: (a) item distribution type (i.e., normal versus uniform; (b) standard deviation of item difficulty (i.e.,.68,.95,.99); (c) number of items or test length (i.e., 50, 100, 200); (d) number of common items (i.e., 10, 20, 30); and (e) sample size (i.e., 100, 300, 500). SIMTEST and BIGSTEPS programs were used for the simulation and equating of 4,860 item data sets, respectively. Results from the five-way fixed effects factorial analysis of variance indicated three statistically significant two-way interaction effects. Simple effects for the interaction between common item length and test length only were interpreted given Type I error rate considerations. The eta-squared values for number of common items and test length were small indicating the effects had little practical importance. The Rasch approach to equating is robust with as few as 10 common items and a test length of 100 items.

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The study investigated five factors which can affect the equating of scores from two tests onto a common score scale. The five factors were: (a) item distribution type (i.e., normal versus uniform; (b) standard deviation of item difficulty (i.e.,.68,.95,.99); (c) number of items or test length (i.e., 50, 100, 200); (d) number of common items (i.e., 10, 20, 30); and (e) sample size (i.e., 100, 300, 500). SIMTEST and BIGSTEPS programs were used for the simulation and equating of 4,860 item data sets, respectively. Results from the five-way fixed effects factorial analysis of variance indicated three statistically significant two-way interaction effects. Simple effects for the interaction between common item length and test length only were interpreted given Type I error rate considerations. The eta-squared values for number of common items and test length were small indicating the effects had little practical importance. The Rasch approach to equating is robust with as few as 10 common items and a test length of 100 items.

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Available abstract

The study investigated five factors which can affect the equating of scores from two tests onto a common score scale. The five factors were: (a) item distribution type (i.e., normal versus uniform; (b) standard deviation of item difficulty (i.e.,.68,.95,.99); (c) number of items or test length (i.e., 50, 100, 200); (d) number of common items (i.e., 10, 20, 30); and (e) sample size (i.e., 100, 300, 500). SIMTEST and BIGSTEPS programs were used for the simulation and equating of 4,860 item data sets, respectively. Results from the five-way fixed effects factorial analysis of variance indicated three statistically significant two-way interaction effects. Simple effects for the interaction between common item length and test length only were interpreted given Type I error rate considerations. The eta-squared values for number of common items and test length were small indicating the effects had little practical importance. The Rasch approach to equating is robust with as few as 10 common items and a test length of 100 items.

Key concepts: Equating, Statistics, Mathematics, Rasch model, Item response theory, Type I and type II errors, Sample size determination, Test (biology)

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