Stability of boundaries between response options of response scales: Does 'very happy' remain equally happy over the years?

The differences between response scales in number and wording of response options make it hard to compare data from survey research and to perform research syntheses. A recent method that we have developed to tackle this problem is rooted in the idea that the transition points on a bounded continuum, on which verbal response options from a primary scale transit from one point to another, for instance from ‘happy’ to ‘very happy’, remain unchanged over time. The idea behind this is that although people may change their perception of, for example, their own happiness intensity over time, they are assumed not to change the degree of appreciation they attribute to the terms used to label response options. This is an important assumption for research syntheses that requires that everything remains unchanged, except for the change of interest. It means that if our method is applied to measurements at distinct points in time, differences in estimates of the mean and standard deviation can be attributed solely to changes in the frequency distributions on the primary scale. In this paper we apply the method to happiness and show that it is reasonable to assume that the transition points between the response options are stable over time. Keywords: verbal response scales; comparability; scale transformation; beta distribution; reference distribution; research synthesi

Bridging Alone: Religious Conservatism, Marital Homogamy, and Voluntary Association Membership

This study characterizes social insularity of religiously conservative American married couples by examining patterns of voluntary associationmembership. Constructing a dataset of 3938 marital dyads from the second wave of the National Survey of Families and Households, the author investigates whether conservative religious homogamy encourages membership in religious voluntary groups and discourages membership in secular voluntary groups. Results indicate that couples’ shared affiliation with conservative denominations, paired with beliefs in biblical authority and inerrancy, increases the likelihood of religious group membership for husbands and wives and reduces the likelihood of secular group membership for wives, but not for husbands. The social insularity of conservative religious groups appears to be reinforced by homogamy—particularly by wives who share faith with husbands

Measures of happiness: Which to choose?

Happiness is defined as the subjective enjoyment of one’s life as a whole, also called ‘life-satisfaction.’ Two components of happiness are distinguished; an affective component (how well one feels most of the time) and a cognitive component (the degree to which one perceived to get what one wants from life). In this chapter, I present an overview of valid measures of these concepts, drawing on the ‘Collection of Happiness Measures’ of the ‘World Database of Happiness’. To date (2016), this collection includes more than twothousand measures of happiness, mostly single direct questions. Links in this text lead to detail about these measures and the studies in this chapter, I describe the differences and discuss their strengths and weaknesse

From Discrete 1 to 10 Towards Continuous 0 to 10: The Continuum Approach to Estimating the Distribution of Happiness in a Nation

Abstract Happiness is often measured in surveys using responses to a single question with a limited number of response options, such as ‘very happy’, ‘fairly happy’ and ‘not too happy’. There is much variety in the wording and number of response options used, which limits comparability across surveys. To solve this problem, descriptive statistics of the discrete distribution in the sample are often transformed to a common discrete secondary scale, mostly ranging from 0 to 10. In an earlier publication we proposed a method for estimating statistics of the corresponding continuous distribution in the population (Kalmijn 2010). In the present paper we extend this method to questions using numerical response scales. The application of this ‘continuum approach’ to results obtained using the often used 1–10 numerical scale can make these comparable to those obtained on the basis of verbal response scales

The medicine is worse than the disease: Comment on Delhey and Kohler’s proposal to measure inequality in happiness using ‘Instrument-Effect-Corrected’ standard deviations.

nequality of happiness in nations can be measured using the standard deviation of responses to surveys questions. The standard-deviation is not quite independent of the mean, being zero when everybody is maximally happy or unhappy while the possible value of the standard deviation is highest when the mean is in the middle of the response scale. Delhey and Kohler see this intrinsic dependency as a problem and propose two ways to compute ‘corrected’ standard deviations. I advise against this medicine. One reason is that there is no real disease, since the presumed problem does not occur with commonly used numerical rating scales of 10 or more steps. The second reason is that one of Delhey and Kohler’s medicines have side effects, their first correction affects the mean and their second correction is based on implausible assumptions. A third reason is that there are better ways to estimate the effect happiness-inequality net happiness-level. Partialling out mean happiness did not affect the non-correlation between inequality of income and inequality of happiness in an analysis of 116 nations

From Discrete 1 to 10 Towards Continuous 0 to 10: The Continuum Approach to Estimating the Distribution of Happiness in a Nation

Happiness is often measured in surveys using responses to a single question with a limited number of response options, such as 'very happy', 'fairly happy' and 'not too happy'. There is much variety in the wording and number of response options used, which limits comparability across surveys. To solve this problem, descriptive statistics of the discrete distribution in the sample are often transformed to a common discrete secondary scale, mostly ranging from 0 to 10. In an earlier publication we proposed a method for estimating statistics of the corresponding continuous distribution in the population (Kalmijn 2010). In the present paper we extend this method to questions using numerical response scales. The application of this 'continuum approach' to results obtained using the often used 1-10 numerical scale can make these comparable to those obtained on the basis of verbal response scales