Correlational finding on Happiness and Current self-characterization
Subject code: S02ab

StudyLaxer (1964): study US 1960
TitleRelation of Real Self-Rating to Mood and Blame and Their Interaction in Depression.
SourceJournal of Consulting Psychology, 1964, Vol. 28, 538 - 546
PublicPsychiatric patients, USA, 196?
SampleNon-probability purposive sample
Respondents N =72

Author's labelSelf blame
Our classificationCurrent self-characterization, code S02ab
Self rating of "What I am really like" on a semantic 
differential scale
a  clear-hazy
b  pleasant-unpleasant
c  valuable-worthless
d  strong-weak
e  deep=-shallow
f  hard-soft
g  hot-cold
i  fast-slow
j  active-passive
Observed distributionRange: 16.67 to 7.75

Observed Relation with Happiness
A-AOL-md-sq-v-10-aAoV=+ p < .005
Evaluative factor (a, b, c:
High self-evaluation goes with better mood
Only among self-blaming patients, not among 
other-blaming patients.
A-AOL-md-sq-v-10-ar=+ p < .05
A-AOL-md-sq-v-10-aAoV=+ p < .025
Potency factor (d,e,f)
High self-evaluation goes with better mood
More so among high self-blaming patients than 
among other-blaming patients.
A-AOL-md-sq-v-10-ar=+ p < .05
A-AOL-md-sq-v-10-aAoV= ns
Activity factor (g,i,j)
Correlation not reported, apparently ns
A-AOL-md-sq-v-10-ar=+ p < .05

Appendix 1: Happiness measures used
CodeFull Text
A-AOL-md-sq-v-10-aSelfreport on single question:

"......overall mood of the past day ......"
( full question not reported.)
10 Complete elation, rapturous joy and soaring ecstasy
9 Very elated and in very high spirits. Tremendous
delight and buoyancy
8 Elated and in high spirits
7 Feeling very good and cheerful
6 Feeling pretty good , "OK"
5 Feeling a little bit low. Just so-so
4 Spirits low and somewhat "blue"
3 Depressed and feeling very low.
Definitely "blue"
2 Tremendously depressed.
Feeling terrible, really miserable, "just awful"
1 Utter depression and gloom. Completely down.
All is black and leaden. Wish it were all over.

Name: Wessman & Ricks' `Elation - Depression Scale'

Appendix 2: Statistics used
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)
rPRODUCT-MOMENT CORRELATION COEFFICIENT (Also "Pearson's correlation coefficient' or simply 'correlation coefficient')
Type: test statistic.
Measurement level: Correlate: metric, Happiness: metric
Range: [-1; +1]

r = 0 no correlation ,
r = 1 perfect correlation, where high correlate values correspond with high happiness values, and
r = -1 perfect correlation, where high correlate values correspond with low happiness values.
Ruut Veenhoven, World Database of Happiness, Collection of Correlational Findings, Erasmus University Rotterdam.