Response Suface Analysis (RSA) is a method from the wider field of Response Surface Methodologies (RSM).
Commensurability explained as briefly as possible is that two scales are measured in the same
units. In the world of Likert-scales this mostly means they are measured on the same number of
Centered on a Common Point
There is a number of ways this can be done.
This post is in essence a summary of McNeish’s (2018) and Raykov and Marcoulides’s (2017) “exchange” on reliability measurement using Cronbach’s alpha. I want to add a few additional perspectives to this topic and provide a short How-To in R.
What is reliability
Many students might learn what reliability is, but once they reach research praxis they often have forgotten the details and what remains is the \(\alpha > .
This is a very short post in which I want to highlight, because I realized that the issue is often overlooked by students when writing up their data. Today I want to highlight the difference between within- and between-subjects errors (With code examples).
Imagine you have data like this example below. Participants responded to a number of mindfulness items multiple times during the day over the duration of a week.
This post focuses on MDS (Also sometimes called smallest space analysis
(Guttman, 1968) or multidimensional similarity structure analysis (Borg
& Lingoes, 1987)) as exploratory tool and a large amount of the information is lifted from Borg and Gronen (2005) which I really recommend for further readings.
Exploratory MDS might seem at first glance like tea-leaf reading, but over the years several rules have been developed that aid in determining structure from the MDS plots.