Literature DB >> 27519780

Confidence Bounds and Power for the Reliability of Observational Measures on the Quality of a Social Setting.

Yongyun Shin1, Stephen W Raudenbush2.   

Abstract

Social scientists are frequently interested in assessing the qualities of social settings such as classrooms, schools, neighborhoods, or day care centers. The most common procedure requires observers to rate social interactions within these settings on multiple items and then to combine the item responses to obtain a summary measure of setting quality. A key aspect of the quality of such a summary measure is its reliability. In this paper we derive a confidence interval for reliability, a test for the hypothesis that the reliability meets a minimum standard, and the power of this test against alternative hypotheses. Next, we consider the problem of using data from a preliminary field study of the measurement procedure to inform the design of a later study that will test substantive hypotheses about the correlates of setting quality. The preliminary study is typically called the "generalizability study" or "G study" while the later, substantive study is called the "decision study" or "D study." We show how to use data from the G study to estimate reliability, a confidence interval for the reliability, and the power of tests for the reliability of measurement produced under alternative designs for the D study. We conclude with a discussion of sample size requirements for G studies.

Keywords:  D study; G study; confidence interval; power; reliability; teaching quality

Year:  2012        PMID: 27519780     DOI: 10.1007/s11336-012-9266-4

Source DB:  PubMed          Journal:  Psychometrika        ISSN: 0033-3123            Impact factor:   2.500


  1 in total

1.  Effects of a motivational climate inntervention for coaches on young athletes' sport performance anxiety.

Authors:  Ronald E Smith; Frank L Smoll; Sean P Cumming
Journal:  J Sport Exerc Psychol       Date:  2007-02       Impact factor: 3.016

  1 in total
  2 in total

1.  Statistical Power in Two-Level Hierarchical Linear Models with Arbitrary Number of Factor Levels.

Authors:  Yongyun Shin; Jennifer Elston Lafata; Yu Cao
Journal:  J Stat Plan Inference       Date:  2017-09-28       Impact factor: 1.111

2.  A Multivariate Generalizability Theory Approach to College Students' Evaluation of Teaching.

Authors:  Guangming Li; Guiyun Hou; Xingjun Wang; Dong Yang; Hu Jian; Weijun Wang
Journal:  Front Psychol       Date:  2018-06-26
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.