A Likert-type Data Analysis Using the Partial Credit Model

• 발행기관: 서울대학교 교육종합연구원
• 저자명: Sun-Geun Baek
• 간행물 정보: 『The SNU Journal of Education Research』Vol.4, 111~125쪽, 전체 15쪽
• 주제분류: 사회과학 > 교육학
• 파일형태: PDF
• 발행일자: 1994.12.30

영문 초록

This study is about examining the possibility of using the partial credit model to solve several problems that occur when we analyze and interpret Likert-type data by traditional methods. The problems are as follows: (i) scores are not directly interpretable and must be examined in the light of a criterion group; (ii) the absence of a zero point handicaps the direct use of individual scores; and (ii) the adequacy of integer scoring, resting upon the validity of the assumption of equal distances between response categories, is not often verified. This study shows that the partial credit model (PCM) solves these problems. In addition, the PCM provides several advantages in the analysis and interpretation for Likert-type data (e.g., item response maps, person and item fit statistics). The PCM also might help to implement the computerized adaptive testing for Likert-type scales.

목차

Ⅰ. Introduction

II. Method

III. Results

IV. Discussion