Happiness Scale Interval Study. Methodological Considerations |
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Authors: | W M Kalmijn L R Arends R Veenhoven |
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Institution: | (1) Erasmus University, Rotterdam, The Netherlands; |
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Abstract: | The Happiness Scale Interval Study deals with survey questions on happiness, using verbal response options, such as ‘very
happy’ and ‘pretty happy’. The aim is to estimate what degrees of happiness are denoted by such terms in different questions
and languages. These degrees are expressed in numerical values on a continuous 0,10] scale, which are then used to compute
‘transformed’ means and standard deviations. Transforming scores on different questions to the same scale allows to broadening
the World Database of Happiness considerably. The central purpose of the Happiness Scale Interval Study is to identify the
happiness values at which respondents change their judgment from e.g. ‘very happy’ to ‘pretty happy’ or the reverse. This
paper deals with the methodological/statistical aspects of this approach. The central question is always how to convert the
frequencies at which the different possible responses to the same question given by a sample into information on the happiness
distribution in the relevant population. The primary (cl)aim of this approach is to achieve this in a (more) valid way. To
this end, a model is introduced that allows for dealing with happiness as a latent continuous random variable, in spite of
the fact that it is measured as a discrete one. The 0,10] scale is partitioned in as many contiguous parts as the number
of possible ratings in the primary scale sums up to. Any subject with a (self-perceived) happiness in the same subinterval
is assumed to select the same response. For the probability density function of this happiness random variable, two options
are discussed. The first one postulates a uniform distribution within each of the different subintervals of the 0,10] scale.
On the basis of these results, the mean value and variance of the complete distribution can be estimated. The method is described,
including the precision of the estimates obtained in this way. The second option assumes the happiness distribution to be
described as a beta distribution on the interval 0,10] with two shape parameters (α and β). From their estimates on the basis
of the primary information, the mean value and the variance of the happiness distribution in the population can be estimated.
An illustration is given in which the method is applied to existing measurement results of 20 surveys in The Netherlands in
the period 1990–2008. The results clarify our recommendation to apply the model with a uniform distribution within each of
the category intervals, in spite of a better validity of the alternative on the basis of a beta distribution. The reason is
that the recommended model allows to construct a confidence interval for the true but unknown population happiness distribution.
The paper ends with a listing of actual and potential merits of this approach, which has been described here for verbal happiness
questions, but which is also applicable to phenomena which are measured along similar lines. |
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