REPORTING LIKERT SCALE RESULTS HOW TO ANALYSE THE

Twenty-eight percent of the 344 articles exhibited congruent interpretations of Likert-scale scores, 45 of the articles exhibited incongruent interpretations, and 27 of the articles exhibited both congruent and incongruent interpretations.This post has been prompted by an edited collection that I was recently asked to review. You should also take a look at the list of additional resources.reliability coefficient cited and the Likert-scale scores reported and interpreted. If that is the case, you will probably be want to skip directly to the part of this post where I talk about a common mistake people make with ordinal data and mean values. In the example, we are going to look at a typical 5 point Likert question.Welcome! Chances are that you landed on this page looking for information on Likert scales and averages. This paper provides an overview of the results displayed in reports generated. The results are back from your online surveys.Now that youвЂ™ve collected your statistical survey results and have a data analysis plan, itвЂ™s time to begin the process of calculating survey results you got back.HereвЂ™s how our Survey Research Scientists make sense of quantitative data (versus making sense of qualitative data), from looking at the answers and focusing on their top research.

HereвЂ™s an example:Indicate what you think about the following statements using the scale below:(1) Strongly Agree (2) Agree (3) Neither agree nor disagree (4) Disagree (5) Strongly Disagree a. Likert scales and ordinal data What are Likert scales?A Likert-type question (or вЂitemвЂ™) asks respondents to select one of several (usually four or five) responses that are ranked in order of strength. Those of you who are unlucky enough to have studied statistics may want to skip to the next section. Those who are not familiar with the fascinating minutiae of quantitative research can find a discussion of Likert scaling and ordinal data in the section that immediately follows. Good visualization choice when the level of detail in a Likert-type scale is unnecessary.Specifically, what sparked my interest was one study in the collection, which used Likert scales to record participantsвЂ™ attitudes towards a certain educational construct.

Interpreting Likert scalesMany researchers tend to use Likert scales to do things that they were never designed to doLikert items and scales produce what we call ordinal data, i.e., data that can be ranked. They are very flexible and very useful, provided you use them carefully. I will not go into any of this in more detail here, but if you want to find out more, this post has some additional information.Likert scales are very frequently used to measure constructs like satisfaction rates, attitudes towards different things, and more. This helps researchers to probe different aspects of the same construct (or вЂ latent variableвЂ™), by putting together information from all the related items. Sometimes, sets of similar items are dispersed in the same questionnaire.

Calculating average scores is one of them, and hereвЂ™s why itвЂ™s wrong:Imagine that ten survey participants were asked about their attitudes towards fish fingers and custard. This, however, is almost the extent of what one canВ do with such data.The problem with Likert itemsВ is that many researchers вЂ“including the ones whose paper prompted this postвЂ“В tend to use them in order to do things that they were never designed to do. In addition to being ranked, ordinal data can be tallied: for example, I might want to divide by sample by age group, count how many people chose each of the responses, and compare results across ages. People who choose response (2) like this snack more than those who choose responses (3), (4) and (5), and so on.

A corollary of the above would be that the distance between вЂagreementвЂ™ and вЂstrong disagreementвЂ™ is four times greater than that between вЂagreementвЂ™ and вЂstrong agreementвЂ™.The mathematical model needs these assumptions in order to work, but they are simply not in the questionnaire design. Firstly, I would be need to assume that the psychological distance between вЂstrong agreementвЂ™ and вЂagreementвЂ™ is the same as that between вЂagreementвЂ™ and вЂno opinionвЂ™. A better wayPlainly put, the option suggested above is statistical nonsense not an optimal interpretation (update: I feel less strongly about this than I used to in 2013, but I still think it is usually wrong).For this interpretation to be valid, I would need to make assumptions like the following: They would therefore pronounce something along the lines of: вЂOur study revealed mild disagreement regarding the palatability of fish and custard ( M=3.5)вЂ™. To do this, I might use the following formula: / (total number of respondents)Going back to the descriptors, I would then ascertain that an вЂaverageвЂ™ response of 3.5 corresponds to something between вЂno opinionвЂ™ and вЂdisagreementвЂ™. вЂMeanвЂ™ is a technical word for вЂaverageвЂ™.

The median is a type of average value, like the mean, except that it shows the number that is exactly in the middle of the data, i.e., at the same distance from the highest and lowest value in the dataset. But please make sure you justify your choice well when you write up your methods section.A safer way forward, if you are interested in finding what the вЂaverageвЂ™ or вЂtypicalвЂ™ response is, is to look at the median response. If you think that they can (and some statistics guidance websites might encourage you to think so), you can still take your chances. If you think they can, do so at your own risk.To put it in the simplest terms possible: Ordinal data cannot yield mean values.

Reporting Likert Scale Results How To Analyse The

You know you should trust me, because I have lots of books on research methods (j/k) On the peer review processAs I wrote at the beginning of this post, one of the papers in the volume that I reviewed made the statistical mistake that I just described, namely it described a set of findings that had been generated by extracting mean values from Likert items. I also recommend reading this overview of Likert scales and this post by Stephen WestlandВ (University of Leeds), for a more nuanced understanding of Likert scaling, and an excellent discussion of how to analyse the data that these scales produce. More to read about Likert scalesIf you came to this page looking for information on Likert scales, you may find the following posts useful: Things you donвЂ™t know about Likert scales, and On Likert scales, levels of measurement and nuanced understandings.

Besides, the findings of this particular study were inconclusive and broadly consistent with what was already known about the phenomenon in question. So, in this case, I decided to let it pass. What can you do if you come across mistakes in published research?So the question I faced was: what should I do when askedВ to provide an informed opinion on the quality of a study that has a major flaw? This was not made any easier by the knowledge that the people responsible for finding this flaw had failed to spot it, or deemed it unimportant. Mistakes in the methodology will, on occasion, slip by. So, rather than double checking on such matters, we tend to focus our feedback on more substantive aspects of the research (e.g., Are the claims commensurate to the scope of the study? Do the findings add significantly to the existing body of knowledge?). Every now and then, reviewers have to take it on faith that the people who conducted a study knew what they were doing, and they must trust that there are no major flaws in the methods.