Abstracts part of this page, full text as PDF files in new window.
Full contents | Contents | |
Chapter 1 |
Plan of this collection |
Abstract Full text |
Chapter 2 |
Selection of studies |
Abstract Full text |
Chapter 3 |
Notation of findings |
Abstract Full text |
Chapter 4 |
Statistics used |
Abstract Full text |
Chapter 5 |
Classification of findings |
Abstract Full text |
Chapter 6 |
Uses of this collection |
Abstract Full text |
Text by Ruut Veenhoven and Wim
Kalmijn (chapter 4), September 2002
Revised version of 'Correlates of Happiness',
volume 1, 'Plan of the data-collection', RISBO, Rotterdam Netherlands, 1994, ISBN
90-72597-47-8.
This catalog is part of the ‘World Database of Happiness’, which contains results of empirical investigations on 'happiness', in the sense of 'life-satisfaction'.
This catalog presents correlational
findings, that is, observations about conditions that differ systematically between
happy and unhappy persons. These findings on happiness are summarized in standard
abstracts, which provide information on measurement, statistics and sampling. These
mini-abstracts are presented in this database.
Abstracts
are rubricated in subject-categories. Within each subject-category, the findings are
ordered by nation; within nations the findings are ordered by year of investigation. This
is to facilitate comparison across time and culture. This catalog presents the
subject-categories in alphabetical order. Browsing the subject-index allows an overview.
The aim is to bring together the
scattered empirical findings on happiness to prepare for synthetic analysis. This endeavor differs from earlier
synthetic studies in that it is more homogenous and
complete
Happiness is defined as
the degree to which an individual judges the overall quality of his life-as-a-whole
favorably. Within this concept two 'components' of happiness are distinguished: hedonic
level of affect (the degree to which pleasant affect dominates) and contentment
(perceived realization of wants). These components represent respectively 'affective' and
'cognitive' appraisals of life and are seen to figure as subtotals in the overall
evaluation of life, called overall happiness.
Happiness as defined here can be measured by means of questioning and hedonic level
also by observations of non-verbal behavior. Though happiness is measurable in principle,
not all the questionnaires and observation schedules used for its measurement are deemed
acceptable. Many measures tap in fact broader phenomena than defined here. These
measures are left out in this database of happiness. All the findings reported here are
based on queries that successfully passed a test for face-validity.
Standard-excerpts of each research-report are made. These excerpts consist of three parts, which can be retrieved independently.
Part 1 Study ·
This part reports never more than one study
Part 2 Measured happiness
If the study contains more than one indicator of happiness, this part reports these separately.
Part 3 Correlational findings (finding-abstracts)
If a study relates happiness to more than one variable, this part presents more than one mini-abstract.
This chapter describes what information is comprised in each of these parts and defines the technical term used.
This chapter starts with a short review of statistical analysis and then presents an overview of statistics used in the excerpts. These statistics are presented in the two schemes below. All are described in an appendix.
Overview of statistics and procedures for bi-variate situationsLevel of measurement of the correlate | Level of measurement of the happiness response | ||
Ordinal | Metric | Dichotomous | |
Metric (§ 4/3.1.3.) | Correlation
coeff. (r) Correlation ratio (R²) Regression coeff. (b) Beta coefficient (b) |
||
Ordinal (§ 4/3.1.2.) | Spearman’s
rank corr. coeff.(rs) Kendall's tau-a (ta) Kendall's tau-b (tb) Kendall's tau-c (tc) Goodman/Kruskal's tau Gamma (G) Somers’ D (Dyx) |
||
Nominal (§ 4/3.1.1) | Chi-square
(c²) Pearson’s C Cramér's V Tschuprow's T |
One-Way Analysis of Variance withmultiple comparisons(BMC, DMRT, SNK) Correlation ratio (E²) | |
Dichotomous (§4/3.1.1) | Difference
in % (D%) Difference modus (DMo) |
Difference
means (DM) - transformed (DMt) - standardized (DMs) Critical ratio (CR) Cohen's d Hedges's g Point biserial correlation (rpb). Correlation ratio (E²) |
Fisher's
2x2 test Odds ratio (OR) Yule's Q Yule's Y Logit coefficient (lgt) Gamma (G) |
Overview of statistics and procedures for multivariate situations
Statistical procedure | Statistics | |
Two or more correlates,
all-metric Single happiness response |
Multiple Regression Analysis | Multiple
correlation coefficient (R) Coefficient of determination (R²) Adjusted coefficient of determination (R_{a}²) Partial regression coefficient (b) Standardized partial regression coeff. (b) Partial correlation coefficients (rpc) |
At least one correlate metric and at least onenominal Single happinessResponse |
Analysis of Covariance (ANCOVA) | Difference
in adjusted means (Ma) Coefficient of determination (R²) Regression coefficient (b) Standardized regression coefficient (b) |
Two or more nominal correlatesSingle happinessResponse | One-Way Analysisof Variance (ANOVA) | F-test and multiple comparisons. |
Loglinear models | ||
Contingency Tables | Chi-square | |
Two or more happiness responses. | Multivariate Analysis ofVariance (MANOVA) | Hotelling's T^{2} |
This catalog stores standard abstracts of correlational research findings. These abstracts are categorized in several ways and can thereby be easily retrieved. Findings are classified for:
These classifications are presented in this chapter
Information about correlates of happiness is of course relevant for a better understanding of happiness and provides information for policies aiming at greater happiness for a greater number. The data in this catalog can contribute to a better understanding of other matters as well.
Methodologically, the data-collection can be used in three ways: for the integration of available research, for theory development and for orientation on new research. All these applications make research-effort more cumulative.
This data collection is meant for the scientific community in the first place. Further it is also of interest for policy makers and the general public
Like any tool, this data-catalog has its pros and cons. Its qualities should be compared to alternative sources of information about research-effort in the field; that is, with narrative literature-reviews on happiness, and with data banks that allow secondary analysis of surveys that involved indicators of happiness