Each element should be followed by the punctuation mark shown here. Earlier editions of the handbook included the place of publication and required different punctuation such as journal editions in parentheses and colons after issue numbers. In the current version, punctuation is simpler only commas and periods separate the elementsand information about the source is kept to the basics. End this element with a period.
Social scientists of all sorts will appreciate the ordinary, approachable language and practical value — each chapter starts with and discusses a young small business owner facing a problem solvable with statistics, a problem solved by the end of the chapter with the statistical kung-fu gained.
This article has been published in the Winnower. You can cite it as: You can also download the published version as a PDF by clicking here. The primary resource available is a paper by Shrout and Fleiss[ 1 ], which is quite dense.
So I am taking a stab at providing a comprehensive but easier-to-understand resource.
For example, if someone reported the reliability of their measure was. The more uniform your measurement, the higher reliability will be.
But when you have research participants provide something about themselves from which you need to extract data, your measurement becomes what you get from that extraction. This process is called coding. Because the research assistants are creating the data, their ratings are my scale — not the original data.
Which means they 1 make mistakes and 2 vary in their ability to make those ratings. An intraclass correlation ICC can be a useful estimate of inter-rater reliability on quantitative data because it is highly flexible. A Pearson correlation can be a valid estimator of interrater reliability, but only when you have meaningful pairings between two and only two raters.
What if you have more? What if your raters differ by ratee? This is where ICC comes in note that if you have qualitative data, e. Unfortunately, this flexibility makes ICC a little more complicated than many estimators of reliability.
While you can often just throw items into SPSS to compute a coefficient alpha on a scale measure, there are several additional questions one must ask when computing an ICC, and one restriction. The restriction is straightforward: The questions are more complicated, and their answers are based upon how you identified your raters, and what you ultimately want to do with your reliability estimate.
Here are the first two questions: Do you have consistent raters for all ratees? For example, do the exact same 8 raters make ratings on every ratee? Do you have a sample or population of raters?
If your answer to Question 1 is no, you need ICC 1.is thoughtful, convincing, insightful, and exploratory. Is firmly grounded in the subject.
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