Correlational finding on Happiness and Number of health complaints
Subject code: H14ab02c

StudyLough et al. (1985): study US 1980
TitleLife Satisfaction Following Heart Transplantation.
SourceHeart Transplantation, 1985, Vol. 4, 446 - 449
PublicHeart transplantation recipients, 7 month to 14 years after transplant, USA, 198?
SampleProbability simple random sample
Non-Response25%
Respondents N =75

Correlate
Author's labelNumber of symptoms
Page in Source 448
Our classificationNumber of health complaints, code H14ab02c
Operationalization
27 item inventory of symptoms related to 
immunosuppressive drugs, side-effects, rated for 
frequency of occurrence 
0  never occurs
4  always occurs

Observed Relation with Happiness
Happiness
Measure
StatisticsElaboration/Remarks
O-QL?-c-sq-v-6-aAoV=- p < .001
O-SQL-c-sq-?-5-aAoV=- p < .01
O-SQL-c-sq-?-5-aRČ=.015
O-QL?-c-sq-v-6-aRČ=.02


Appendix 1: Happiness measures used
CodeFull Text
O-QL?-c-sq-v-6-aSelfreport on single question:

"....... current quality of life"
(full lead items not reported)
1
2
3
4
5
6
(response options not reported)
O-SQL-c-sq-?-5-aSelfreport on single question:

".....satisfaction with current quality of life ...."
(Full question not reported.)
1
2
3
4
+
(Response options: not reported)


Appendix 2: Statistics used
SymbolExplanation
AoVANALYSIS of VARIANCE (ANOVA)
Type: statistical procedure
Measurement level: Correlate(s): nominal, Happiness: metric.
In an ANOVA, the total happiness variability, expressed as the sum of squares, is split into two or more parts, each of which is assigned to a source of variability. At least one of those sources is the variability of the correlate, in case there is only one, and always one other is the residual variability, which includes all unspecified influences on the happiness variable. Each sum of squares has its own number of degrees of freedom (df), which sum up to Ne -1 for the total variability. If a sum of squares (SS) is divided by its own number of df, a mean square (MS) is obtained. The ratio of two correctly selected mean squares has an F-distribution under the hypothesis that the corresponding association has a zero-value.

NOTE: A significantly high F-value only indicates that, in case of a single correlate, the largest of the c mean values is systematically larger than the smallest one. Conclusions about the other pairs of means require the application of a Multiple Comparisons Procedure (see e.g. BONFERRONI's MULTIPLE COMPARISON TEST, DUNCAN's MULTIPLE RANGE TEST or STUDENT-NEWMAN-KEULS)
COEFFICIENT of DETERMINATION
Type: test statistic
Measurement level: Correlates: all metric, Happiness: metric
Range: [0; 1]

Meaning:
RČ = 0 « no influence of any correlate in this study has been established.
RČ = 1 « the correlates determine the happiness completely.
Source:
Ruut Veenhoven, World Database of Happiness, Collection of Correlational Findings, Erasmus University Rotterdam.
https://worlddatabaseofhappiness.eur.nl