Maste Kasa

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Marriage and Psychological Well-Being: Some Evidence on Selection into Marriage

Author(s): Arne MastekaasaSource: Journal of Marriage and Family, Vol. 54, No. 4 (Nov., 1992), pp. 901-911Published by: National Council on Family RelationsStable URL: http://www.jstor.org/stable/353171.

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2/12

ARNE

MASTEKAASA

University f

Oslo

Marriage

and

Psychological Well-Being:

Some Evidence

on

Selection

Into

Marriage

Higherpsychological

well-beingamong

married

as opposedto unmarried ersonsmay be due to

social selection

into

marriage,

or to

marriage f-

fects

(social

causation).

From the selection

hy-

pothesis

it

follows

that

well-being

at one time

point

be

positively

related

o

the

subsequent rob-

ability

of marrying.

Using

ransition

atemethods

(Cox regression)

n a

sample

of

9,

000

unmarried

persons,

strong

and

significant

relationships

re

found.

The

predictivepower

of

the

well-being

measures remains stable

throughout

the

2- to

4-year

period of

observation.

t

is concluded hat

selection

mayplay

an

important art

in

producing

the

oft-observed

association between

marital

status

and

well-being.

One

of

the more well

established

indings

n

re-

search

on

mental health

is the

relationship

be-

tween marital

tatus

on

the

one hand and various

measures

of

psychologicalwell-being

and

psychi-

atric

symptoms

n

the

other.

Typically

t

has been

found

that

the

currently

married

njoy

the

most

favorable

position,

the

divorcedand widowed

are

generallyworstoff, withthe nevermarriedn an

intermediate

osition.

The most

impressive

eature

of

this

relation-

ship

s its

consistency

cross

ime,

space,

and

mea-

surement

procedures.

Similar results

have been

obtained

with

attitudinal

well-being

measures

(Blom

&

Listhaug,

1988;

Clemente&

Sauer,

1976;

Mastekaasa&

Moum,

1984;

Robinson

&

Shaver,

1973), symptom inventories (Bradburn, 1969;

Pearlin

&

Johnson, 1977;

Srole,

Langner,

Michael,

Opler,

&

Rennie,

1962),

mental

hospital-

ization rates

(Gove,

1972a; Martin, 1976;

Mastekaasa,

1984;

Odegaard,1971),

and suicide

rates

(Gove,

1972b;Mastekaasa,

1984).

Some

re-

cent results

may

indicate hat these differences

n

subjective

well-being

have

been

declining

n

recent

years,

at least

in

the United

States

(Glenn

&

Weaver,

1988;

Lee,

Seecombe,

&

Shehan,

1991).

However,

data

from

two

European

countriesdo

not

show

the

same trend

(Veenhoven, 1984;

Mastekaasa,

1984,

1988).

Whatever

he most recent

trends

in the rela-

tionship

between

marital tatusand

psychological

well-being,

he

problem

of how to

interpret

t in

causal

terms remains

unsolved.

Basically,

one

may

argue

hat

(a)

marital

tatus

has

some effect

on

well-being; (b) well-being

has

an effect

on

marital

tatus;

or

(c)

both

well-being

and

marital

status are

influenced

by

one

or more common

causes.

In the literature

a)

is often referred

o

as a

social

causation

hypothesis,

where

b)

and

(c)

may

be referred o as socialselectionhypotheses.In-

tuitively,

both

types

of

hypotheses

eem

reason-

able,

and

they

are

not

mutually

xclusive.

t

is not

difficult

to

imagine

that a

spouse may provide

practical,

emotional,

and other

support

in

the

presence

of

stresses

and

strains,

support

that

is

not

as

readily

available

or

those

who

are

not

mar-

ried

(or

live as

married).

t is

also

quite ikely

hat

happy

and

cheerful

people

are

regarded

as

more

attractive

marriagepartners

han

brooding

and

epartment

of

Sociology, University

of

Oslo,

P.O. Box 1096

Blindern,

N-317

Oslo, Norway.

Journal

of

Marriage

nd the

Family

54

(November1992):

901-911

901


3/12

902

Journal

of

Marriage

nd the

Family

depressive

ones. Thus the observed

relationship

between marital status

and

psychological

well-

being

could

well be

the

joint

result

of social selec-

tion and causationprocesses.

Most

sociological

discussions

of the social

causation

and social selection

hypotheses

never-

theless

conclude hat socialselection

processes

re

of little

or no

importance

n

explaining

he associ-

ation

between marital

status and

psychological

well-being(Menaghan,

1985;

Glenn

&

Weaver,

1988;

Gove,

Hughes

&

Style,

1983),

although

selectioncould

be

more

important

n

connection

with

serious

mental

disorders

(cf.

Pearlin

&

Johnson,

1977).

The

empirical

vidence,

however,

is

generally

of

a

highly

indirect

kind,

and there-

fore alsoquite nconclusive. nparticular,mostof

the relevant tudiesuse

only

cross-sectional

ata,

which

makes

causal

nferencesdifficult.

If

the

association

between

subjective

well-

being

and

marital

status

is at least

in

part

the

result

of

a selection

process,

we

should

expect

measures

of

subjective

well-being

aken

at

one

time to

predict

the

probability of

changes

in

marital

tatus

at

later ime

points;

people

with ow

levels

of

well-being

hould

be

more

likely

to

re-

main unmarried

r to divorce

f

already

married.

In this studyI test the hypothesisas it applies

to

the never married.More

specifically,

using

a

sample

of

about

9,000

unmarried

men and

women,

I

examine

whether

measures

f

well-being

made at

one

time

point

predict

transition

nto

marriage

n

the

following

months

and

years.

A

statistical

elationship

etween

psychological

well-

being

and

the

subsequent robability

f

marrying

provides

upport

or

the selection

hypothesis,

but

does

not

imply

rejection

of

the

social

causation

hypothesis.

As

noted

above,

social selectionand

social

causation

may

both contribute

o

the dif-

ference in well-beingbetween marriedand un-

married

people.

PREVIOUS

ESEARCH

As far

as the

present

author

s

aware,

ongitudinal

studies

of

the

relationship

between

subjective

well-being

or

mental

health)

and the

probability

of

transition

nto

marriage

ave

not

been

reported

in

the

literature.

However,

Menaghan

(1985)

analyzed

he

relationship

between

depressive

af-

fect

and

subsequent

divorce.

Her

sample

con-

sistedof 790married

eople

whowere nterviewed

in

1972

and

again

in

1976.

Using ordinary

east

squares,

marital tatus

n

1976

(whether

divorced

or

still

married)

was

regressed

n 1972

measures

of

depression,

marital

distress,

and other

relevant

variables.No significant ffect of depressionwas

found.

However,

he

number

of

people divorcing

in

the

4

years

between1972

and 1976was

only

32

(or

4%).

Any analysis

based

on

a

comparison

of

these

32

persons

with those who did

not divorce

s

therefore

highly susceptible

o

random

sampling

and

measurement rrors.

Moreover,

use of linear

regression

r

discriminant

nalysis

s

problematic

when the

dependent

variable is

so

extremely

skewed as

is the case

in

this

study

(Goodman,

1976).

As

noted

above,

most

empirical

tudies

on

the

socialcausation-selectionssuearebasedon cross-

sectionaldata.

Gove et al.

(1983)

argue

that

if

a

social selection

process

s

operating,

he

associa-

tion

between marital status and

subjective

well-

being

should be

substantially

educed

f

one

con-

trols

or

problems

an individual

xperienced

s

a

child.

The conclusiondrawn

by

Gove et al.

(1983,

p. 125)

was

that the

relationship between

hild-

hood

problems

and adult

mental

health]

is

quite

weak and

not

strong

enough

to

alterthe relation-

ship

between

present

marital status and

mental

healthsubstantially. At best, this can be inter-

preted

as evidence

against

social selectioneffects

due

to

childhood

experiences;

he

possibility

of

selectiondue

to

genetic

factors remains.

Equally

important,

he

validity

of

retrospective

measures

of

childhood

experiences

s

obviously

doubtful.

A third

approach

o

the social causation-selec-

tion

issue

is

to

compare

differences

between

mar-

ried and

unmarried

ersons

across

age categories.

If

a

selection

process

is

operating (and

in

the

absence

of

complicating

ohort

effects)

one

would

expect

he association

between

marriage

nd well-

beingto increasewithage,as thehappiestandthe

most

marriageable

eople

are

gradually

elected

out

of

the unmarried

ategory.

Littleevidence

or

selectionhas been

found n studies

employing

his

approach

(Glenn

&

Weaver, 1988; Mastekaasa,

1988).

Glenn

and

Weaver

also carriedout

cohort

analyses

based

on the

same

type

of

reasoning;

n

these

analyses,

oo,

no

evidence

or

selectionwas

found.

Needless

to

say,

inferencesbased

on

this

type

of

analysis

are

highly

indirect and rest

on

several

trong

and dubious

assumptions.

Someresearchers

ave

argued

hatthe

subjec-

tive

well-being

f

widows

and

widowers

s of

par-

ticular interest

if one

wants

to

disentangle

he


4/12

Marriage

and

Psychological Well-Being

903

underlying

ausal

processes.

The

argument

s

that

one

may

assume a

priori

that selection

nto

the

widow(er) ategory

s

not

significantly

nfluenced

by social selection(Blom& Listhaug,1988).Ac-

cordingly,

widowed

persons

should

not

differ

from

married

nes,

controlling

or

age

and other

relevant

variables.Durkheim's

1970) analysis

of

suicide

provides

an

argumentalong

these

lines.

However,

n

modern western

societies

there

is a

considerable umber

of

widowed

persons

who

re-

marry; although

there

is

no

selection

into

the

population

of

widowed

persons,

here

may

be

dif-

ferentialselection

of

happy

and

unhappypeople

out

of

it.

To

sum

up,

the

empirical

tudiesare

not

very

conclusive.In

particular,

ittle or no

evidence s

available

n

possible

election ffects

n

the transi-

tion

from

unmarried

o

married.

SAMPLE AND VARIABLES

The

data used

in

this

paper

were

collected

n

con-

nection with a

medical

screening

of

the entire

population

of

one

of

Norway's

19 counties. The

county

of

Nord-Tr6ndelag

s

comparatively

ural

and

sparsely

populated

(6

people

per square

kilometer),witha totalpopulationof 127,000 in-

cluding

children).

During

the

period

January

1984

to

February

1986

all

adults

aged

20 and

above

were

screened

for

hypertension,

diabetes,

and

lung

disease. On

arrival

at

the

screening, participants

were

sup-

posed

to

hand

in

a

one-page

self-administered

questionnaire

which

had

been distributed

y

mail

as a

part

of

the

invitation

to

participate

n

the

screening

Questionnaire ).

A

second

question-

naire

(QuestionnaireI)

was handed

o

all

partici-

pants

as

they

left

the

screening,

with

the

instruc-

tion to fill inthisquestionnaires soon aspossible

and return

t

by

mail to

the

investigators.

The

subpopulation

of

interest

to

us is never

married

persons

n

the

20-39

age range,

all

in

all

13,276

people.

I

exclude

n

most

analysespersons

reporting

hat

they

lived

together

with

a

person

of

the

opposite sex,

as well

as those

living per-

manently

n

institutions.This

brings

the size

of

our

subpopulation

down

to

9,683;

3,252

women

and

6,431

men.

Generally

peakingparticipation

nd

response

rates in

the Nord-Trdndelag tudy were very

satisfactory;

8%0

anded

n

Questionnaire

,

and

75%0

eturned

Questionnaire

I.

For our

subpopu-

lation

of

relatively

young

and never

married

respondents,

however,

the

results were

not

as

good.

Overall

usable

Questionnaire

data were

obtained rom2,089womenand4,125 men,yield-

ing fairlyacceptable

esponse

rates

of

64.3%

and

64.1%,

respectively.

As

far as the

Questionnaire

II

dataare

concerned,however,

he

response

ates

are less than

satisfactory;

0.20%o

or

women

and

43.6% for

men.

Questionnaire

contained

only

a

single

well-

being item,

whereas everal

additonal tems

were

included

in

Questionnaire

I.

Due to the

low

response

ate

for

Questionnaire

I,

we

shall

never-

theless

have

o

rely

o a

considerable xtent

on

the

single

Questionnaire

item. We

may

use the

some-

whatricher

Questionnaire

Idatato

get

some dea

of how

vulnerablehe

resultsare

to

the

reliance

n

the

single-item

measure.

The

questionnaire

data

provide

information

about marital

status,

psychological

well-being,

and other variablesat

one

specific

ime

point.

By

making

use

of

public marriageregisters

we

are

able to addinformationabout

changes

n

marital

status

in

subsequent

years,

more

specifically

or

the

years

1984

to

1987.

Since

the

screening

tself

was

carried ut

during

he

period

January

1984 o

February 1986, we have data on subsequent

changes

n

marital

tatus

for

a

period

varying

be-

tween 22

and

47

months,

depending

on

when

a

particular

ndividual

was screened.

Using

this

information,

we

define our

depen-

dent

variable

MARRIAGE

o

take

the

value 1 if

an individual

marries

during

he

time

of

observa-

tion,

and

to

be 0

otherwise.The

TIME

between

the

start of the

period

of

observation,

hat

is,

the

screening

and the

collection

of

questionnaire

data,

and

marriage

s

measured

n

months.

For

those who

do

not

marry

during

the

period

of

observation, hat is, for so-calledcensoredobser-

vations,

TIME

is

defined as the

length

of

the

observational

eriod.

The

independent

ariable

f

primary

nterest s

psychological

well-being.

As noted

above,

Ques-

tionnaire

I

contained

a

single

well-being

tem,

more

specifically

a

standard

7-point

overall

life

satisfaction tem.

The

response

ategories

were

all

labeled,

ranging

from

very

satisfied

to

very

dissatisfied.

We refer to

this

one-item

measure

as SATISF.

QuestionnaireI containedan identicalsatis-

faction

measure,

but

also some

additonalwell-

being

items

allowing

us to

constructa

four-item


5/12

904

Journal

of

Marriage

and the

Family

additive

ndex

(WELLB).

In

addition

o

the two

identical atisfaction

measures,

he index ncludes

two

semanticdifferential ike items

measured

on

7-point

scales:

verystrong

and

fit-very

tired

and

rundown,

and

very depressed-very

happy.

The

index

score is the arithmetic

average

of

the

responses

on

the

four items

(if

a

respondent

did

not

answerone

or two of

the

items,

she is

given

her

average

core

on

the

remaining

tems).

The correlations

among

the

four

well-being

itemsare

n

the

.48

to

.70

range,

and

the

reliability

(Cronbach'sa)

of the

summated

scores is

.82.

Factor

analysis

(principal

axes

factoring)

of

the

items

provide

clear

evidence

of

unidimensionality

(an

eigenvalue

f

2.6

for

the first factorand

.6

for

thesecond).If theQuestionnaireand II satisfac-

tion

items are assumed

o

be

equally

reliable,

he

test-retest orrelation

of

.70

between

these items

provides

an estimate

of

the

reliability

f

the

single

item SATISF measure.The internal

consistency

and test-retestestimatesare

in

line with

results

reported

n

the

quality

of

life literature

e.g.,

Ab-

bey

&

Andrews, 1985;

Diener,

1984;

Larsen &

Diener,

1985). Although

these results

must

be

considered

uitesatisfactory y

most

standards,

t

should

be

noted that less

than

perfect reliability

can be

expected

to

bias coefficients downward

andto increase tandard rrors,

herebymaking

t

more

difficult

to

obtain

evidence

of

selectionef-

fects.

In

addition

o

the

well-being

measures,

we

in-

clude

some

additional

ndependent

variables

as

controls.

The selection of

control variables is

based

on

previous

research

on

transitions

nto

marriage,

ubject,

of

course,

to

the limitations

f

the

current

data

set

(Elder

&

Rockwell,

1976;

Hogan,

1978;

Waite&

Spitze, 1981).

First

of

all,

we

may

note that

all

analyses

are

carried ut separatelyormenand women.Ageis

also

partly

aken

into

consideration

y

means

of

subgroupanalyses,

but

in

additionmost

analyses

include he

variable

AGE,

measured

n

years.

The

probability

f

marriage

an

be

expected

o

differ

between

sparsely

and more

denselypopu-

lated

areas.

In

particular,

elective

migration

of

young

womento

the

cities

may

create mbalances

in

the

marriage

market.

Using

a

standard for

classification

evelopedby

the

Norwegian

Central

Bureau of

Statistics,

the

variable CENTRAL

distinguishes

etween

relatively

central

or

urban

(value 1) and relatively peripheral (value 0)

municipalities.

Previous research

has

demonstrated hat one

of the most

importantpredictors

of

marriage

s

the extent to

which

a

person

is

engaged

n

ac-

tivities that

consume

periods

of

time

during

the

transition

to

adulthood,

such as an

additional

year

of

schooling,

service

n

the

military,

and

im-

migration

rom

abroad

(Hogan, 1978,

p.

169).

Using

the

gainfully

employed

as a

reference

ate-

gory,

we

include

dummy

variables or

education/

military

service

(EDUCMIL)

and

not

working

(NOT

WORK).

We use

two health

measures. LL

takes

on

the

value

1 if

the

respondent

eports

hat she

or

he

has

any

diseasewhichrestricts

daily

activities

n

some

way,

and 0

otherwise.

SUBH

is

a

measure

f

self-

assessedhealth,withvalue1for poor and not

quite good

healthand 0

otherwise.

We do not

include

measures

of

occupational

and educational

attainmentas

independent

ari-

ables. For

the

relatively

young sample

analyzed

here,

use

of

these variables s

fairlyproblematic.

Moreover,

previous

esearchhas shown

hat

these

variableshave

very

weak

relationships

with

sub-

jective well-being.

Omitting

these

variables is

therefore

not

likely

o

biasthe

estimated

ffects

of

well-being

on

the

probability

f

marrying.

Descriptive

tatistics

or

the

independent

ari-

ables are

given

in Table 1.

TABLE

.

DESCRIPTIVETATISTICS

Women Men

Values

M

SD

M

SD

CENTRAL

0-1

.749 .434 .700

.458

AGE

20-39

26.172 4.875

26.769 5.007

SUBH

0-1 .087 .281 .079

.269

ILL

0-1

.126

.332 .165

.371

NOTWORK

0-1 .308

.462

.137

.343

EDUCMIL

0-1

.234 .423

.145

.352

SATISF

1-7

5.623 1.060 5.528 1.128

WELLB 1-7 5.307 .902 5.353 .873

MARRIAGE 0-1 .113 .317 .077 .267

TIME

1-47

35.258 8.017

35.257 7.504

STATISTICAL

ETHODSND

MODEL

PECIFICATION

The

question

asked

in

this

study

is

whether

sub-

jective

well-being

affects the

probability

of

marry-

ing.

Since

most

individuals do not

marry

during

the

period

of

observation,

most

of

the

observa-

tions are censored.

Furthermore,

he

length

of

the

observational

period

varies

(from

22

to 47

months).The researchquestion s thereforebest

answered

by

applying

methods

for

the

analysis

of


6/12

Marriage

nd

Psychological

Well-Being

905

event

history

or

durationdata.

More

specifically,

we

may

use

so-called Cox

regression,

or

semi-

parametric

roportional

hazards

stimation.

In this method,the rateof transition theso-

called hazard

rate)

from

the

unmarried o

the

married

tate can

be

expressed

as

(cf.

Blossfeld,

Hamerle,

&

Mayer, 1989):

7r(t

x)

=

ro(t)exp(x'O)

(1)

or,

equivalently,

ln[7r(t

x)]

=

ln[ro(t)]

+

x'3

(2)

In

these

equations,

t

is

time

since

the

screening

and

x

is a

vector

of

independent

ariables;

r0

nd

0

are

parameters.

The

logarithmically

rans-

formed transition rate for an individual is

specified

as

the sum of two

terms.

The

first

term,

ln[or(t)],

allows

the

transitionrate

to

vary

over

the time of

observation,

but the exact

functional

form of

this time

dependence

does

not

have

to

be

specified since

so-called

partial

ikelihood stima-

tion

is

used).

The

second

erm,

x'P,

allows

he

log

of

the transition ate to

vary

as a linearfunction

of the

independent

variables

the

x

vector).

Ex-

ponentiating

he estimated

coefficients,

they

can

be

interpreted

s follows:

For

each

unit

ncrease

n

an independentvariable, the transition rate is

multiplied by

its

exponentiated

coefficient

(Allison,

1984,

p.

28).

Roughly

speaking

the

estimated

hanges

n

the transition

ate

can

be in-

terpreted

s

changes

n

the

probability

of

making

a

transition. f we

find,

for

instance,

hat

the esti-

mated

coefficient

for

a

7-point

satisfactionmea-

sure

is

.20,

corresponding

o

an

exponentiated

coefficient

of

1.22,

the

interpretation

s that a unit

increase

n

satisfaction s

associated

with a

22%

increase

n

the

probability

f

marrying.

As noted

above,

the

partial

ikelihood

method

allows us to estimatethe effects of a set of in-

dependent

variables

without

having

to

specify

how the

transition ate

varies

over

ime.

However,

the method

s basedon the

assumption

f

propor-

tional

likelihoods;

that

is,

the

proportional

dif-

ference

in

the transitionrate

between

categories

on

an

independent

variable

should be

constant

over

time.

Returning

o our

exampleabove,

a unit

increase

n

satisfaction

houldbe

associatedwith

a

22% increase

in

the

probability

of

marrying

throughout

he

period

of

observation.If the

ef-

fect of

satisfactiondeclines

over

time,

the

propor-

tionallikelihood

assumption

s violated.

The

time

dependence

of

the

effect is

by

no

meansa

purely

echnical

matter,

however.

argue

below

that a selection

theory

of

the

relationship

between

marriage

nd

well-being

mplies

hat

the

predictive owerof psychologicalwell-beingmea-

suresdoes not declineover

time.

The time

dependence

of the

well-being

effect

canbe

analyzed

n several

ways.

One

possibility

s

to

expand

the hazard model

by including

a

specific

time

dependence arameter

moreor

less

like an

interactioneffect

in

an

ordinary

inear

regression

model.

In some of the

models

esti-

mated

below,

the

effect

of the

well-being

measure

is

specified

as:

Owellb

=

ao0

+

CZ[ln(t)

- 2.4849]

(3)

The effect of well-being

(fwellb)

is allowed to de-

pend

on the

log

of the time

since

the

screening

t)

and

c1

can be

interpreted

as the

change

in

the

well-being

effect

corresponding

o a

doubling

of

the time

since

he

screening;

a

gives

he

estimated

effect of

psychological

well-being

fter 12

months

(i.e.,

when

[ln(t)

-

2.4849]

equals

0).

If

the

estimateof

a

ca

is not

significant

we

may

take

this

as an

indication hat the

effect

of

satisfaction

s

approximately

onstant

over

the

period

of

obser-

vation.

To check the robustnessof the results,I also

examine he time

dependence

ssue

by

estimating

series

of

models

in

which

the

time

between the

well-being

measurement

and

the

start

of

the

period

of

observation s

gradually

ncreased.In

the first

analysis,

he

period

of

observation

tarts

at thetime of the

well-being

measurement

i.e.,

at

the time

of

the

screening).

n

the

second

analysis,

those who

marry

within

a

6-month

period

ollow-

ing

the

initial

measurement

re

excluded

rom

the

analysis.

We ask in

effect: Does

overall

life

satisfaction

predict

the

probability

of

marrying,

given that a person has not marriedwithinthe

first

6

months

after

answering

he

well-being

ues-

tions.

This

analysis

s

then

repeated

by

excluding

those who

marry

within

12,

18,

and 24

months

following

he

screening,

espectively.

The

present

analyses

may

give

an

indication

of

the existenceand

magnitude

of

selection

effects,

but

it

provides

very

little

information

about the

actual

content

of

a

selection

process.

In the

first

place,

we

have

data

on

individuals

nly,

whereas

marriage

s the result

of

an interaction

etween

at

least)

two

persons.

Neitherdo we

have

informa-

tion

about

possible

relevant

behavioral dif-

ferences

between

happy

and

unhappy people.


7/12

906

Journal

of Marriage

and the

Family

Simply

appearing

o be

happy

and

cheerful

may

make

a

person

more

attractive as

partner

or

spouse.

But low

well-beingmay

also

be

correlated

withcharacteristicsikepassivity,ntroversion, r

low

interpersonal

competence

(Diener,

1984;

Costa &

McCrae,

1980;

cf. also

Hansson, Jones,

&

Carpenter,

1984).

Moreover,

happy

persons

may

be

more

optimistic

about

the

future,

and

thereforemore

ready

o run the

risk of a marital

relationship.

Although

the

data

do not

allow a more de-

tailed

investigation

f the

hypothesized

election

processes,

he

above

remarks t

least serve

o

sen-

sitize us

to

the

possibility

hat

selection

processes

may

be

different

for

men

and

women,

and for

persons

at different

age

levels. The directionof

potential

differences

re,

however,

not

easily

pre-

dicted.

To the

extent

that traditional ex roles are

still

important,

personal

characteristics

like

passivity

or

introversion

may

be

particularly

damaging

o

men,

whereas

generally ppearing

o

be

happy

and

cheerful

may

be more

mportant

or

women.

Another

reason for

expecting

different

selec-

tion

processes

or

men and

women

has

been

sug-

gested

by

Bernard

1972).

She

argues

that men

tend to prefermarriagewithsociallyand intellec-

tually

inferior

women.

Characteristics

ike in-

telligence

and

independence

hus

may

reduce a

woman's

probability

f

finding

a

suitable

partner,

whereas

they

may

have the

opposite

effect

for

men.

Selection

processes

may

also

differ between

people

at

different

age

levels. The

personality

nd

behavioral

haracteristicshat

makea

20-year-old

man an

attractive

marriage

artner

to perhaps

n

18-year-old

woman) may

be

different from the

characteristics

hat

are most

important

for

a

35-year-oldman. Inaddition, hemarriageate t-

self

depends

of

course

very

muchon

age, typically

following

an

inverted

U-shape.

In

Norway,

the

probability

of

marriage

s

greatest

or

persons

n

their

mid-20s.

To

allow for

differences

n

the

selection

proc-

ess,

the

models

are

estimated

eparately

or

men

and

women

and

(with

the

exception

noted

below)

for two

different

age

categories

of

approximately

equal

size

(20-25

and

26-39

years

of

age).

Within

each

of

these

categories

heeffects of

the

indepen-

dentvariables

re not assumed o

depend

on

age.

The

effect of

age

on the

logarithm

of the

transi-

tion rate is

assumed o

be linear.

We

expect

the

direct

effect of

age

to be

positive

n the

20-25

age

intervaland

negative

n the

26-39 interval.

To

obtain more

stable estimates

n the more

detailedanalysesof the time dependenceof the

well-being

ffect,

the

sample

s

not subdivided

y

age.

However,

the

analyses

are still carried

out

separately

or men and women.As a second

best

solution

to the

problem

of

age

effects,

we use a

so-called stratified

analysis. Age

is

grouped

nto

four strata

20-24,

25-29,

30-34,

and

35-39),

and

the

marriage

ate as well as the time

dependence

of this rate is

allowed

to

vary

between he strata

(cf.

Blossfeld,

et al.

1989,

p.

149ff).

THEPREDICTIVEOWERF

THE

WELL-BEING

EASURES

Table

2

contains

results

rom

separateregression

analyses

of

four

subsamples,

women divided

nto

the 20-25 and 26-39

age

categories,

and men

divided

into

the same

categories.

The

estimated

effect

of

overall ife satisfaction

s

positive

n

all

four

subsamples

nd

clearlysignificant

n two

of

them. The

clearest

evidence

or

a

selection

effect

is

found

for

women

n

the 20-25

age

category

and

for

men 26-39

years

of

age.

Using

a .05

signifi-

cance evel(anda one-tailed est, which s appro-

priatehere),

he effect

of

satisfaction

n the rate

of transition nto

marriage

s

significant

or

women

n the

26-39

agecategory,

oo.

In the model

used

here,

the

effect

of

satisfac-

tion

is

allowed o declineoverthe

period

of obser-

vation.

The

TIME

variable

s

scaled so

that

the

estimated coefficient

for

SATISF

can

be inter-

preted

as the

effect

of

satisfaction

when

TIME

s

equal

to

12

months.

There s

no

evidence

hat the

effect

of

satisfaction

s

really

declining

as

a

func-

tion of time. In none of the four

regression

analysess thecoefficient or theinteractionerm,

SATISF

x

In(TIME),

ignificant;

and

it has the

expected negative

sign

in

only

two

of the four

analyses.

In view

of

these

results,

t

may

be

preferable

o

assume

hatthe

effects

of

satisfaction

reconstant

over

time,

and

to estimate

he model without an

interaction

term. The estimates

appearing

in

parentheses

re

based

on

that model.

(This

mod-

ification

of

the

model affects

the

estimated

oeffi-

cients for the

control

variables

very

little,

and a

new set of estimates s thereforenot shown.)

As one

would

expect given

the small and un-

stable

nteraction

ffects,

the main

pattern

of the


8/12

Marriage

and

Psychological

Well-Being

907

TABLE 2. Cox

REGRESSION

OF MARRIAGE ON OVERALL LIFE SATISFACTION AND CONTROLS

Women

Men

20-25

Years

26-39 Years

20-25 Years 26-39

Years

b Sb b bb b Sb b Sb

CENTRAL

.1022 .1832

-.3393

.2581 -.1423

.1661 .0264

.1808

AGE

-.0271 .0608 -.1149

.0380 .1919 .0590 -.1072 .0252

SUBH

.0600 .3750

-.0573

.4751 .3971 .3560 .4579 .3026

ILL

-.2957

.3191

.1734 .3722 -.8837 .3077 -.4117 .2735

NOTWORK

-.0846 .1986 -.4031 .2827 -.2081 .2473 -.0510 .2740

EDUCMIL

-.1360

.1843 .2081 .3562 .0925 .1843 .0468 .3492

SATISF

.3015*** .0935 .2198* .1267 .0235 .0953 .2133** .0829

(SATISF)a

(.3118***) (.0826)

(.1868)

(.1231) (.0709)

(.0740)

(.1923*)

(.0813)

SATISF

x

In(TIME)

.0298

.1067 -.1971 .1500 .0824 .1070 -.1360 .0897

Log-likelihood

-114.5241 -476.1625 -1252.4554

-1067.2962

n

1,251

838

2,118 2,007

Proportion marrying

.130

.088

.081 .073

Response

ate

.618

.684

.633 .650

aEstimate based

on

the

assumption

f constanteffect of satisfaction

no

time

dependence).

Probability levels for SATISF and SATISF x In(TIME) coefficients (one-tailed t tests):

*p

< .05.

**p

Documents

Maste Kasa