I studied mathematics and policy research. I am interested in socio-economic research, survey methodology and social policy. As a senior volunteer of the World Database of Happiness of the Erasmus Happiness Research Organization (EHERO) of the Erasmus University Rotterdam I did PhD-research on the improvement of the comparability of survey results accross surveys in the period 2011-2015. Address: https://nl.linkedin.com/in/tineke-de-jonge-359b774
Many trend studies draw on survey data and compare responses to questions on the same topic that ... more Many trend studies draw on survey data and compare responses to questions on the same topic that has been asked over time. A problem with such studies is that the questions often do not remain identical, due to changes in phrasing and response formats. We present ways to deal with this problem using trend data on life satisfaction in Japan as an illustrative case. Life satisfaction has been measured in the Life in Nation survey in Japan since 1958 and the question used has been changed several times. We looked at three methods published by scholars who tried to reconstruct a main trend in life satisfaction from these broken time-series, coming to different conclusions. In this paper we discuss their methods and present two new techniques for dealing with changes in survey questions on the same topic.
__Abstract__ Survey data are often used for comparison purposes, such as comparisons across natio... more __Abstract__ Survey data are often used for comparison purposes, such as comparisons across nations or comparisons over time. Ideally, this would require equivalent questions and equivalent responses options to these questions. Yet there is a lot of variation in the response scales used, which, for example, differ in the number of response options used and the labelling of these options. This difference in items is no problem when surveys are analysed separately, but it limits the comparability of findings gathered in different surveys that used different items for the same topic. This reduces our accumulation of knowledge and calls for methods to transform ratings on different scales to attain comparable results and to correct for effects of changes in measurements and other influencing factors. Conventional methods to transform ratings on different response scales to a common one, such as the commonly used Linear Stretch Method, fall short to overcome the comparability problem caused by the non-uniformity of survey items. The weaknesses of these early transformation methods also appear when the transformed scores are compared to average ratings on 0-10 numerical scales in the same country in the same year. The shortcomings of conventional methods instigated the development of new techniques, which will be discussed in this thesis. This thesis is divided into four parts. In the first part we give a comprehensive description of the comparability problem and why conventional methods fall short to solve this problem. Each of the three parts that follow focuses on a successive innovation to improve the comparability of survey findings with different survey items.
Scholars often want to know what the interrelations of the means in subgroups of the population a... more Scholars often want to know what the interrelations of the means in subgroups of the population are, for example from the perspective of inequality or marginalization. When using a discrete response scale with a limited number of response options it will be a difficult task to derive this information from the survey results. This difficulty can be overcome if the Reference Distribution Method is applied to these survey results. Once a continuous distribution has been found to estimate a population mean for life satisfaction over time, it is also possible to estimate the means for subgroups of a population such as the least satisfied and the most satisfied part. We use the topics satisfaction with life and satisfaction with how democracy works in Western Europe, Southern Europe and Eastern Europe to demonstrate how the Reference Distribution Method can be used for this purpose.
This chapter starts with an introduction to the incomparability problem and an overview of the di... more This chapter starts with an introduction to the incomparability problem and an overview of the diversity in survey items. This is followed by a description of the problem of incomparability of the time series on life satisfaction in the USA, Japan and The Netherlands to illustrate the problem. Next two conventional methods for scale transformation are described: the Linear Stretch Method and the Semantic Judgment of Fixed Word Value Method. We explain why they fall short to solve the comparability problem and conclude that these shortcomings require further investigations and innovative solutions to solve them.
The labeling of the anchor points of a response scale may tempt the judges participating in scale... more The labeling of the anchor points of a response scale may tempt the judges participating in scale intervals studies to assign zero-width intervals to these points by choosing the upper and lower bound equal to an extreme of the continuum. The phenomenon of assigning zero-width intervals occurs more frequently when extreme wording is used for an anchor point label and when the response scale consists of more than five response options. Although all-inclusive response scales would encompass the full spectrum of possible experiences, there uses is likely to make anchor points redundant for part of the respondents using such a response scale.
Research has shown that keywords make a difference, for instance that questions using the keyword... more Research has shown that keywords make a difference, for instance that questions using the keyword ‘happiness’ elicit somewhat more positive responses than otherwise similar questions on ‘life satisfaction’. This difference is typically attributed to the topic addressed in the lead question, but there could also be a difference in the interpretation of the response options of the rating scale, for instance when ‘very happy’ denotes a lower degree of well-being than ‘very satisfied’. We present a method to explore the extent to which this difference in interpretation of response options occurs. We illustrate this method by applying it to equivalent response scales for happiness and life satisfaction with response options labeled in Dutch, Spanish and English. We conclude that the interpretation of the scales by respondents has to be examined and discussed carefully in advance before mutually comparing survey results across populations and nations for happiness and life satisfaction.
The main aim of the Happiness Scale Interval Study (HSIS) was to improve the comparison of happin... more The main aim of the Happiness Scale Interval Study (HSIS) was to improve the comparison of happiness across nations. To do this it is necessary to understand the difference in interpretation of the response options of the same item in different languages and to determine whether differences in leading questions affect the interpretation of the response options, given in different languages, to identical response scales.
The Scale Interval Method is a new method to investigate which intervals on a continuum from 0 to... more The Scale Interval Method is a new method to investigate which intervals on a continuum from 0 to 10 are assigned to verbally labeled response options when asked in different questions and languages. The method is very useful for getting insight in the extent to which the interpretation of response options depends on language, culture, and the context of the scale. The Reference Distribution Method is a new method to make the responses to different survey questions on the same topic comparable. The method is based on the idea that, for a given year and a given population, the distribution means after scale transformation for similar questions about happiness asked in different representative surveys should be approximately the same irrespective of the primary response scales used. In this method, the boundaries between the response options are derived from a reference distribution. The method can be applied to combine time series from different surveys on the same topic which span d...
Results from the Happiness Scale Interval Studies (HSIS) can be used to address a number of quest... more Results from the Happiness Scale Interval Studies (HSIS) can be used to address a number of questions. A selection of these questions is used for explanatory purposed in this book. We use results from HSIS-studies conducted in The USA, The Netherlands and Spain. An overview of the recruitment process for judges for these studies is given, followed by a short discussion of these judges representativeness of the general population.
We applied the Reference Distribution Method to pool time series on life satisfaction in the USA,... more We applied the Reference Distribution Method to pool time series on life satisfaction in the USA, Japan, The Netherlands and Spain, using results from the World Values Survey to derive reference distributions from. This resulted in consistent time series spanning almost 60 years for Japan, 40 years for The Netherlands and 35 years for the USA and Spain. Life satisfaction in Japan and The Netherlands was almost equal in the eighties, but at present differs more than one point in favor of The Netherlands. Life satisfaction in Spain reached its lowest value of 6.0 in 2012, but has increased since then to 6.3 in 2015.
Many trend studies draw on survey data and compare responses to questions on the same topic that ... more Many trend studies draw on survey data and compare responses to questions on the same topic that has been asked over time. A problem with such studies is that the questions often do not remain identical, due to changes in phrasing and response formats. We present ways to deal with this problem using trend data on life satisfaction in Japan as an illustrative case. Life satisfaction has been measured in the Life in Nation survey in Japan since 1958 and the question used has been changed several times. We looked at three methods published by scholars who tried to reconstruct a main trend in life satisfaction from these broken time-series, coming to different conclusions. In this paper we discuss their methods and present two new techniques for dealing with changes in survey questions on the same topic.
__Abstract__ Survey data are often used for comparison purposes, such as comparisons across natio... more __Abstract__ Survey data are often used for comparison purposes, such as comparisons across nations or comparisons over time. Ideally, this would require equivalent questions and equivalent responses options to these questions. Yet there is a lot of variation in the response scales used, which, for example, differ in the number of response options used and the labelling of these options. This difference in items is no problem when surveys are analysed separately, but it limits the comparability of findings gathered in different surveys that used different items for the same topic. This reduces our accumulation of knowledge and calls for methods to transform ratings on different scales to attain comparable results and to correct for effects of changes in measurements and other influencing factors. Conventional methods to transform ratings on different response scales to a common one, such as the commonly used Linear Stretch Method, fall short to overcome the comparability problem caused by the non-uniformity of survey items. The weaknesses of these early transformation methods also appear when the transformed scores are compared to average ratings on 0-10 numerical scales in the same country in the same year. The shortcomings of conventional methods instigated the development of new techniques, which will be discussed in this thesis. This thesis is divided into four parts. In the first part we give a comprehensive description of the comparability problem and why conventional methods fall short to solve this problem. Each of the three parts that follow focuses on a successive innovation to improve the comparability of survey findings with different survey items.
Scholars often want to know what the interrelations of the means in subgroups of the population a... more Scholars often want to know what the interrelations of the means in subgroups of the population are, for example from the perspective of inequality or marginalization. When using a discrete response scale with a limited number of response options it will be a difficult task to derive this information from the survey results. This difficulty can be overcome if the Reference Distribution Method is applied to these survey results. Once a continuous distribution has been found to estimate a population mean for life satisfaction over time, it is also possible to estimate the means for subgroups of a population such as the least satisfied and the most satisfied part. We use the topics satisfaction with life and satisfaction with how democracy works in Western Europe, Southern Europe and Eastern Europe to demonstrate how the Reference Distribution Method can be used for this purpose.
This chapter starts with an introduction to the incomparability problem and an overview of the di... more This chapter starts with an introduction to the incomparability problem and an overview of the diversity in survey items. This is followed by a description of the problem of incomparability of the time series on life satisfaction in the USA, Japan and The Netherlands to illustrate the problem. Next two conventional methods for scale transformation are described: the Linear Stretch Method and the Semantic Judgment of Fixed Word Value Method. We explain why they fall short to solve the comparability problem and conclude that these shortcomings require further investigations and innovative solutions to solve them.
The labeling of the anchor points of a response scale may tempt the judges participating in scale... more The labeling of the anchor points of a response scale may tempt the judges participating in scale intervals studies to assign zero-width intervals to these points by choosing the upper and lower bound equal to an extreme of the continuum. The phenomenon of assigning zero-width intervals occurs more frequently when extreme wording is used for an anchor point label and when the response scale consists of more than five response options. Although all-inclusive response scales would encompass the full spectrum of possible experiences, there uses is likely to make anchor points redundant for part of the respondents using such a response scale.
Research has shown that keywords make a difference, for instance that questions using the keyword... more Research has shown that keywords make a difference, for instance that questions using the keyword ‘happiness’ elicit somewhat more positive responses than otherwise similar questions on ‘life satisfaction’. This difference is typically attributed to the topic addressed in the lead question, but there could also be a difference in the interpretation of the response options of the rating scale, for instance when ‘very happy’ denotes a lower degree of well-being than ‘very satisfied’. We present a method to explore the extent to which this difference in interpretation of response options occurs. We illustrate this method by applying it to equivalent response scales for happiness and life satisfaction with response options labeled in Dutch, Spanish and English. We conclude that the interpretation of the scales by respondents has to be examined and discussed carefully in advance before mutually comparing survey results across populations and nations for happiness and life satisfaction.
The main aim of the Happiness Scale Interval Study (HSIS) was to improve the comparison of happin... more The main aim of the Happiness Scale Interval Study (HSIS) was to improve the comparison of happiness across nations. To do this it is necessary to understand the difference in interpretation of the response options of the same item in different languages and to determine whether differences in leading questions affect the interpretation of the response options, given in different languages, to identical response scales.
The Scale Interval Method is a new method to investigate which intervals on a continuum from 0 to... more The Scale Interval Method is a new method to investigate which intervals on a continuum from 0 to 10 are assigned to verbally labeled response options when asked in different questions and languages. The method is very useful for getting insight in the extent to which the interpretation of response options depends on language, culture, and the context of the scale. The Reference Distribution Method is a new method to make the responses to different survey questions on the same topic comparable. The method is based on the idea that, for a given year and a given population, the distribution means after scale transformation for similar questions about happiness asked in different representative surveys should be approximately the same irrespective of the primary response scales used. In this method, the boundaries between the response options are derived from a reference distribution. The method can be applied to combine time series from different surveys on the same topic which span d...
Results from the Happiness Scale Interval Studies (HSIS) can be used to address a number of quest... more Results from the Happiness Scale Interval Studies (HSIS) can be used to address a number of questions. A selection of these questions is used for explanatory purposed in this book. We use results from HSIS-studies conducted in The USA, The Netherlands and Spain. An overview of the recruitment process for judges for these studies is given, followed by a short discussion of these judges representativeness of the general population.
We applied the Reference Distribution Method to pool time series on life satisfaction in the USA,... more We applied the Reference Distribution Method to pool time series on life satisfaction in the USA, Japan, The Netherlands and Spain, using results from the World Values Survey to derive reference distributions from. This resulted in consistent time series spanning almost 60 years for Japan, 40 years for The Netherlands and 35 years for the USA and Spain. Life satisfaction in Japan and The Netherlands was almost equal in the eighties, but at present differs more than one point in favor of The Netherlands. Life satisfaction in Spain reached its lowest value of 6.0 in 2012, but has increased since then to 6.3 in 2015.
This book describes why conventional methods fall short to solve the comparability problem and in... more This book describes why conventional methods fall short to solve the comparability problem and introduces three successive innovations to overcome these shortcomings. Comparability of results from different surveys using different items for the same topic is greatly hampered by the differences in response scales used. This reduces our accumulation of knowledge and has challenged researchers in the field of survey research for long to develop appropriate methods to transform ratings on different scales to attain comparable results and to correct for effects of changes in measurements and other influencing factors. The three innovations described in this volume are applied to data on happiness and life satisfaction, show better comparability of the survey results concerning the perceptions and opinions of people over time and across nations and at an increased opportunity for meta-analysis on these results.
This book describes why conventional methods fall short to solve the comparability problem and in... more This book describes why conventional methods fall short to solve the comparability problem and introduces three successive innovations to overcome these shortcomings. Comparability of results from different surveys using different items for the same topic is greatly hampered by the differences in response scales used. This reduces our accumulation of knowledge and has challenged researchers in the field of survey research for long to develop appropriate methods to transform ratings on different scales to attain comparable results and to correct for effects of changes in measurements and other influencing factors. The three innovations described in this volume are applied to data on happiness and life satisfaction, show better comparability of the survey results concerning the perceptions and opinions of people over time and across nations and at an increased opportunity for meta-analysis on these results.
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