Can IRT Solve the Missing Data Problem in Test Equating?

Can IRT Solve the Missing Data Problem in Test Equating?

In this paper test equating is considered as a missing data problem. The unobserved responses of the reference population to the new test must be imputed to specify a new cutscore. The proportion of students from the reference population that would have failed the new exam and those having failed the reference exam are made approximately the same. We investigate whether item response theory (IR...

A method to solve the problem of missing data, outlier data and noisy data in order to improve the performance of human and information interaction

Abstract Purpose: Errors in data collection and failure to pay attention to data that are noisy in the collection process for any reason cause problems in data-based analysis and, as a result, wrong decision-making. Therefore, solving the problem of missing or noisy data before processing and analysis is of vital importance in analytical systems. The purpose of this paper is to provide a metho...

How IRT can solve problems of ipsative data in forced-choice questionnaires.

In multidimensional forced-choice (MFC) questionnaires, items measuring different attributes are presented in blocks, and participants have to rank order the items within each block (fully or partially). Such comparative formats can reduce the impact of numerous response biases often affecting single-stimulus items (aka rating or Likert scales). However, if scored with traditional methodology, ...

Psychological Methods How IRT Can Solve Problems of Ipsative Data in Forced-Choice Questionnaires

Can Big Data Solve the Fundamental Problem of Causal Inference?

© American Political Science Association, 2015 PS • January 2015 75 ........................................................................................................................................................................................................................................................................................................ ...................................