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Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social and Economic Research, University of Essex Question ordering effects on the reporting of fertility intentions and close social networks

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Page 1: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Understanding Society Conference25 July 2013

Paul Mathews

Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social and Economic Research, University of Essex

Question ordering effects on the reporting of fertility intentions and close social networks

Page 2: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Question ordering - Context Effects

Change in the answers to a survey questionnaire as a function of the previous items in the questionnaire’ Tourangeau et al, 2003

Examples Context Effects

Vodka or beer questions influences rating to how ‘Germanic’ is wine drinking? (Schwarz, Munkel and Hippler, 1990)

Life Satisfaction preceding Marriage Satisfaction r = 0.32, Marriage satisfaction preceding Life Satisfaction r = 0.67 (Schwarz, Strack and Mai 1991)

Frequency of Context Effects General Social Survey (US) batteries of questions rotated. Only

4% of questions effected by placement (Smith, 1988) Needs to be a conceptual link

Page 3: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Question ordering - Context Effects

Question priming bias as domain sampling

Particularly in multipurpose longitudinal research (Time series - Change over time? Changes in preceding questions?)

Plausible risk

Page 4: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Why are fertility intentions important?

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Page 8: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

“The changing face of London: A baby boom is sending the city’s planners back to the drawing board”

The Economist 28th Jan 2012

“By 2015-16 greater London will need around 70,000 more school places”

Page 9: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Measurement problems…

Uncertainty / ambivalence

Context dependent… Preferences change over time

Age, ageing, life course, cohort, period Is there a ‘correct’ age to measure FP?

Experience of children Partnership and partner’s preferences Competing preferences

economic, cultural, leisure etc…

Because fertility preferences are so context dependent, then will the context in the questionnaire matter i.e. preceding questions?

Page 10: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

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Page 12: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Millennium Cohort Study – Wave 1

“How long did the labour last?” “Which, if any, of the following

types of pain relief did you have at any time during labour?”

Before asking “Do you plan to

have any more children?”

Page 13: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Social networks

Numerous concepts and operationalisations Flows through social networks Social capital Strength of weak ties Relatedness

At risk of context effects? E.g. prime a domain such as ‘work’ or ‘family’… does this influence who is ‘in’ your social network

Page 14: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

My empirical work

Page 15: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Mortality experiments

Randomised (systematically identical) groups. o Treatments: priming questions then fertility questionso Controls: fertility questions then priming questions

Adult (own) mortality priming questions • 11 Questions• “What age do you expect to be when you die?”

Data collected 2006 and 2008-09 Published - Mathews and Sear 2008

Students internet experiment

Results: Significant increase in MALE ideal numbers of children. No effect for females •

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Page 16: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Why?

Not mutually exclusive… Fatigue? Negative mood? Old age support (in adult prime)? First item in battery of fertility preferences? (DHS ideal

question) Own mortality is a ‘shock’ to non-decision decision?

(Competing preferences, cultural output and sociological modernity)

Social Psychological - Terror Management Theory (TMT) social immortality?

Evolutionary biology – Life History Theory (perceived risky environment should alter reproductive strategy)?

Sheer chance?!• Replication

Page 17: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Innovation Panel experiment

Waves 4 and 5 of Innovation Panel sub sample of 1,500 households - NOT STUDENTS!

Randomisation at household level

Controls Wave 4: Experiment after mental wellbeing

“I've been able to make up my own mind about things”

5 point scale: [All of the time – None of the time] Wave 5: Experiment after GHQ

“Have you recently been feeling reasonably happy, all things considered?”

4 point scale 1 More so than usual 4 Much less than usual

Page 18: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Two question ordering ‘treatments’

Fertility Intentions: “Do you think you will have any (more) children?”

[1 Yes, 2 Self / partner currently pregnant, 3 No] if the answer is yes “How many (more) children do you

think you will have?”

Close social network (i.e. 3 closest friends) ‘Please choose the three people you consider to be your

closest friends... They should not include people who live with you but they can include relatives’

Sex, Age, relatedness, frequency of contact, how far away they live etc

‘Is this friend a relative?’ [ 1 Yes, 2 No]

Page 19: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

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Descriptive statistics

Observations 696 Wave 4 N=409, Wave 5 N=287

223 individuals measured twice (27 changed their minds on wanting children)

Background demographics remain very similar across waves - Male 60%, Age mean 37.5 (SD 13.4) median 39 (split dummies in model), Parents 48%, Employed 72% (11% full time students), Married 45%, Lives with a parent 22%, sibling 14%.

Page 20: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Fertility intentions27 close social

network questions

(Nine questions for three

friends)

Fertility intentions questions

wave 4 ‘Make mind’ or wave 5

‘happiness’

(No social network

questions)

Page 21: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Social network

Close social network questions

1 or 2 fertility intentions questions

wave 4 ‘Make mind’ or wave 5 ‘happiness’

(No fertility intentions questions)

Page 22: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Results – Fertility intentions

  All participants - reporting expecting

a(nother) child

Just unmarried participants - same

  Wave 4 Wave 5 Wave 4 Wave 5

Treatment –preceding close social network

34.4% 50%

Control 1 – make mind up question

27.0% 37.1%

Control 2 – general happiness question

/ /

Number of participants

409 225

P-value of a t-test between control and treatment within the wave (Note: without Bonferoni correction)

0.052 0.03

Page 23: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Results – Fertility intentions

  All participants - reporting expecting

a(nother) child

Just unmarried participants - same

  Wave 4 Wave 5 Wave 4 Wave 5

Treatment –preceding close social network

34.4% 32.7% 50% 48.8%

Control 1 – make mind up question

27.0% / 37.1% /

Control 2 – general happiness question

/ 33.6% / 47.4%

Number of participants

409 287 225 160

P-value of a t-test between control and treatment within the wave (Note: without Bonferoni correction)

0.052 0.44 0.03 0.43

Page 24: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Results – Fertility intentions

  All participants - reporting expecting

a(nother) child

Just unmarried participants - same

  Wave 4 Wave 5 Wave 4 Wave 5

Treatment –preceding close social network

34.4% 32.7% 50% 48.8%

Control 1 – make mind up question

27.0% / 37.1% /

Control 2 – general happiness question

/ 33.6% / 47.4%

Number of participants

409 287 225 160

P-value of a t-test between control and treatment within the wave (Note: without Bonferoni correction)

0.052 0.44 0.03 0.43

Page 25: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Results – Social network

  All participants - reporting a relative in their close social

network

  Wave 4 Wave 5

Treatment –preceding fertility intentions question

31.4% 26.5%

Control 1 – make mind up question

29% /

Control 2 – general happiness question

/ 25%

Number of participants 409 287

P-value of a t-test between control and treatment within the wave (Note: without Bonferoni correction)

0.30 0.38

Page 26: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Conclusions

Fertility intentions at risk of preceding questions Plausible risk...

Little evidence relatedness (or any other characteristics) of their close social network at risk of preceding questions

Important to construct and read questionnaires as a whole

Repeated measures: Replication, replication, replication

Page 27: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Acknowledgements

Participants in all studies

Maria Iacovou, University of Essex

Rebecca Sear, London School of Hygiene and Tropical Medicine

Ernestina Coast London School of Economics and Political Science

UK Economic and Research Council for funding

UKHLS Methodological Advisory Committee for accepting proposal

ISER and HMRC secondment

Page 28: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

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Page 29: Understanding Society Conference 25 July 2013 Paul Mathews Knowledge, Analysis and Intelligence Directorate, HM Revenue and Customs Institute of Social

Conclusions

Fertility intentions at risk of preceding questions Plausible risk...

Little evidence relatedness (or any other characteristics) of their close social network at risk of preceding questions

Important to construct and read questionnaires as a whole

Repeated measures: Replication, replication, replication