Correlational finding on Happiness and subject: Current contacts with friends

StudyRotondi et al. (2016): study IT 2016
TitleConnecting Alone: Smartphone Use, Quality of Social Interactions and Well-Being.
SourceWorking Paper: Politecno di Milano and University of Milan Bicocca, Department of Management, Economics and Industrial Engineering (DIG), 2016, Italy
Public18+ aged, general public, Italy, 2016
SampleProbability multistage stratified area sample
Non-Response
Respondents N =144809

Correlate
Author's labelTime spent with friends
Page in Source 6-11,14
Our classificationCurrent contacts with friends
Operationalization
Single question:
"How often in your free time do you meet your friends?"
6 Every day
5 More than once a week
4 Once a week
3 Less than 4 times per month
2 Few times per year
1 Never
Observed distributionM=4.19; SD=1.37

Observed Relation with Happiness
Happiness
Measure
StatisticsElaboration/Remarks
O-SL?-?-sq-n-11-aBeta=+.12 p < .01
ALL
O-SL?-?-sq-n-11-aBeta=+.28 p < .01
AT LEAST ONCE A WEEK
O-SL?-?-sq-n-11-aBeta=+.21 p < .01
MORE THAN ONCE A WEEK

Beta's controlled for:
- smartphone use
- gender
- education
- employment
- marital status
- volunteering
- religiousness

Less positive among users of smartphone for web 
searches: interactions significantly negative
O-SL?-?-sq-n-11-ab-iv=+.90 ns


Appendix 1: Happiness measures used
CodeFull Text
O-SL?-?-sq-n-11-aSelfreport on single question:

'......on general estimate of life-satisfaction...'
(full text not reported)
0 entirely dissatisfied
1
2
3
4
5
6
7
8
9
10 fully satisfied


Appendix 2: Statistics used
SymbolExplanation
b-ivREGRESSION COEFFICIENT in regression ananlysis with instrumental variable as one or more explanatory variables
Type: test statistic.
Correlate level: metric, Happiness level: metric
Theoretical range: unlimited

The instrument must be correlated with the endogenous explanatory variables, conditionally on the other covariates. If this correlation is strong, then the instrument is said to have a strong first stage. A weak correlation may provide misleading inferences about parameter estimates and standard errors.
The instrument cannot be correlated with the error term in the explanatory equation, conditionally on the other covariates. In other words, the instrument cannot suffer from the same problem as the original predicting variable. If this condition is met, then the instrument is said to satisfy the exclusion restriction.


See Mardia Kent & Bibby (1979): Multivariate Analysis
BetaSTANDARDIZED REGRESSION COEFFICIENT by LEAST SQUARES (OLS)
Type: test statistic.

Measurement level: Correlates: all metric, Happiness: metric.
Range: [-1 ; +1]

Meaning:
beta > 0 a higher correlate level corresponds to a higher happiness rating on average.
beta < 0 a higher correlate level corresponds to a higher happiness rating on average.
beta = 0 no correlation.
beta = + 1 or -1 perfect correlation.
Source:
Ruut Veenhoven, World Database of Happiness, Collection of Correlational Findings, Erasmus University Rotterdam.
https://worlddatabaseofhappiness.eur.nl