Correlational findings | World Database of Happiness

Study Rehdanz & Maddison (2009): study XZ Germany West 1994

Public: Adults, general public, West-Germany, 1994-2004
Sample
Respondents: N = 23014
Non Response: na
Assessment: Interview: face-to-face

Correlate

Authors's Label

Building type

Our Classification

Operationalization

Self report on building type the respondent lives:
a Agricultural building
b Single or double house
c Terrace house
d Flat in building with 3 to 4 flats
e Flat in building with 5 to 8 flats
f Flat in building with 9 or more flats
g Flat in high rise building
h Else (reference category)

Observed Relation with Happiness

Happiness Measure

Statistics

Elaboration / Remarks

O-SLW-c-sq-n-11-d

OPRC = - ns

REGRESSION coefficient in ORDERED categorical PROBIT analysis.

Only the sign of the computed coefficient is informative.

Happiness is an ordered categorical variable. Higher categories correspond to being more happy.

OPRC < 0 indicates that the probability of being beyond a chosen happiness category decreases and the probability of being at or below that category increases when

1) the corresponding metric correlate increases
2) the corresponding category of a categorical correlate is compared to the reference category.

OLRC > 0 indicates that the probability of being beyond a chosen happiness category
increases and the probablity of being at or below that category decreases when

1) the corresponding metric correlate increases
2) the corresponding category of a categorical correlate is compared to the reference category.

Agricultural building (vs else) (-.02)

O-SLW-c-sq-n-11-d

OPRC = + ns

REGRESSION coefficient in ORDERED categorical PROBIT analysis.

Single or double house (vs else) (+.12)

O-SLW-c-sq-n-11-d

OPRC = + ns

REGRESSION coefficient in ORDERED categorical PROBIT analysis.

Terrace house (vs else) (+.11)

O-SLW-c-sq-n-11-d

OPRC = + ns

REGRESSION coefficient in ORDERED categorical PROBIT analysis.

Flat in building with 3 to 4 flats (vs else) (+.08)

O-SLW-c-sq-n-11-d

OPRC = + ns

REGRESSION coefficient in ORDERED categorical PROBIT analysis.

Flat in building with 5 to 8 flats (vs else) (.05)

O-SLW-c-sq-n-11-d

OPRC = + ns

REGRESSION coefficient in ORDERED categorical PROBIT analysis.

Flat in building with 9 or more flats (vs else) (+.01)

O-SLW-c-sq-n-11-d

OPRC = + ns

REGRESSION coefficient in ORDERED categorical PROBIT analysis.

Flat in high rise building (vs else) (+.07)

OPRC's controled for:
- affected by noise and air pollution
- socio-economic characteristics
- demographic characteristics
- housing characteristics
- residential characteristics

OPRC's cannot be interpreted as absolute effect sizes.