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RE: st: RE: Mean test in a Likert Scale

From   "David Radwin" <>
To   <>
Subject   RE: st: RE: Mean test in a Likert Scale
Date   Fri, 31 Aug 2012 09:32:31 -0700 (PDT)


It may be the case that not labeling the middle points of a scale, as in
your first example, justifies the assumption of equal spacing (deltas).
But the literature suggests that verbally labeling all points on a scale,
as in your second example, leads to more reliable measurement. See, for

Alwin DF, Krosnick JA. 1991. The reliability of survey attitude
measurement: The influence of question and respondent attributes. Sociol.
Methods Res. 20:139-81.

David Radwin
Senior Research Associate
MPR Associates, Inc.
2150 Shattuck Ave., Suite 800
Berkeley, CA 94704
Phone: 510-849-4942
Fax: 510-849-0794

> -----Original Message-----
> From: [mailto:owner-
>] On Behalf Of Rob Ploutz-Snyder
> Sent: Friday, August 31, 2012 9:13 AM
> To:
> Subject: Re: st: RE: Mean test in a Likert Scale
> My 2 cents...when designing these sorts of instruments...
> I was trained that a true likert scale doesn't label each of the
> points in the 5-point (or other) scale, but instead has only TWO
> labels at each extreme.  For example:
> I like Statalist..............      Completely Disagree   1  2  3  4
> 5    Completely Agree
> This is in CONTRAST to a scale that would label each and every point
> (sometimes called "likert-type" or "modified-likert") for example:
> 1=completely disagree
> 2=disagree
> 3=neutral
> 4=agree
> 5=completely agree
> With true likert scales, while still not continuous in scale, the
> distance between each category in a true likert scale is not
> subjective.  The delta between "1" and "2" is the same as the delta
> between "2" and "3" etc.  and it is assumed that survey respondents
> can appreciate this.  The same cannot be assumed about the difference
> between "completely disagree" and "disagree" being equal to the delta
> between "disagree" and "neutral."
> So in that way, a  true-likert scale removes some of the subjectivity
> on the deltas and seems to achieve a more proper ordinal scale as
> opposed to purely categorical.
> Still doesn't justify using parametric statistical techniques...
> However, most well-vetted Sociology or Psychological instruments are
> designed to use multiple questions that, together, are used to measure
> a particular construct.  Social scientists don't usually intend to
> compare responses on single questions, but instead ask many questions
> that cluster together, often verified by exploratory or confirmatory
> factor analysis, where "factor scores" are then created to capture the
> overall construct of interest.  These factor scores can be derived by
> different methods, the simplest being a mean of the items that cluster
> together, but usually by more sophisticated regression-based methods
> that weigh each item according to how well it correlates with the
> overall factor structure.  These factor scores are continuously
> scaled, unlike the individual items that were used to derive them, and
> it is these factor scores that are often analyzed by various
> parametric statistical techniques.
> Whether or not the factor scores  are normally distributed in the
> population (the real question) is dependent on the particulars of each
> research study, but I don't categorically deny that the assumption is
> invalid.

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