The NLSY79 Child Assessments

NLS Summer Research Workshop

Paula BakerCHRR at The Ohio State University

July 2007

Aim & scope of the Child assessments

Primary Aim - To assess key aspects of physical, cognitive, social and emotional development

What assessments are used?

What do they measure?

How were they collected?

What scores are available?

Types & modes of assessments

Two types of assessments:

1. Established scales2. Other indicators of child wellbeing – some

scaled, some individual items

Three modes of data collection:

1. Interviewer-administrated to child (in Child Supplement)

2. Mother report (in Mother Supplement)3. Interviewer observation

The assessment domains: What do they measure?

Cognitive – memory; math & reading achievement, word reception & recognition

Socioemotional – developmental milestones; temperament; perceived self-competence

Behavioral – prosocial; behavior problems; peer conflicts; risk taking

Physical Health & Development – hgt & wgt measurements; self-reports

Cognitive: Interviewer-administered

Memory - Wechsler Digit Span

Achievement/Ability:

PIAT Math

PIAT Reading

Vocabulary recognition/retention: PPVT-R

Cognitive assessments for little kids

Short-term memory:

McCarthy Verbal Memory

Memory for Location

Receptive vocabulary:

Body Parts

Socioemotional Assessments

Motor & Social Development (MSD) – from NHIS

Temperament (What My Child is Like) – from Rothbart, Campos, and Kagan

Self-Perception Profile for Children (SPPC) – Harter scales

Other socioemotional measures

Child moods: Child 10-14 in Child Self-Administered Supplement

Risk aversion scales: Child 10-14 report in CSAS

Shyness: Interviewer-report in Child Supplement

Psych referral: Mother-report

Behavioral, Mother Report

Behavior Problems Index (BPI)

Measures incidence and severity of child behavior problems

Global Measure & subscales:

1. antisocial

2. anxious or depressed

3. hyperactive

4. headstrong

5. dependent

6. peer conflicts Trichotomous vs Dichotomous

The HOME-SF Mother Report

Mother Report

emotional and verbal responsiveness

maternal acceptance of and involvement with her child

organization of the environment

presence of materials for learning

variety of stimulation

The HOME Interviewer Observations

Interviewer observes physical environment & parent-child interactions

Interviewer Observations – not available if …

No interaction observed

No visit to the home (interview by phone)

Child too young for assessment

The HOME-SF scales

Three Scales:

Overall (conservative imputation for missing)

Emotional Support

Cognitive Stimulation

Pattern of Assessment Administration

Eligible ages Assessment

1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 Parts of the Body 1–2 1–2

Memory for Locations 8 mos–3 yrs

(8 mos–3 yrs)

McCarthy Verbal Memory Subscale 3–6 (3–6) (4–6) (3–6) (3-6)

What I Am Like (Self-Perception Profile) 8 + 8 + 8 + 8 + 8-14 12-14 12-14 12-14 12-14 12-14

WISC-R Digit Span Subscale 7 + 10–11

(7 +) 10–11 (7 +)

10–11 (7 +)

10-11 (7-14)

7-11 7-11 7-11 7-11 7-11

PIAT Math & Reading 5+ 5 + 5 + 5 + 5-14 5-14 5-14 5-14 5-14 5-14

PPVT-R 3 + 10–11 (3 +)

10–11 (3 +) 3 + 10-11

(3-14) 10-11 (4-14)

4-5, 10-11

4-5, 10-11

4-5, 10-11

4-5, (6-9), 10-11

HOME environment All ages All ages All ages All ages 0-14 0-14 0-14 0-14 0-14 0-14 Temperament 0–6 0–6 0–6 0–6 0-6 0-6 0-6 0-6 2-6* 2-6* Motor & Social

Development 0–3 0–3 0–3 0–3 0-3 0-3 0-3 0-3 2-3*

Behavior Problems 4 + 4 + 4 + 4 + 4-14 4-14 4-14 4-14 4-14 4-14

Assessment Scores

What types of scores are available? Summary scores for each assessment See tables & appendices in users guide

How are they computed? Procedures in users guide

Conservative imputation for missing data: HOME, BPI, SPPC

Not all assessments are normed: No normed scores for Temperament or SPPC

Raw & standardized scores for Digit Span (no pctile)

Norms – Std vs %ile

Types of scores: Standardized vs Percentile vs Raw

Standard Score

equal-interval measure

one of the most common metrics

can be compared across tests

can be arithmetically manipulated

Percentile Score

ordinal scale

more intuitive

caution against using to manipulate scores by differencing or taking an average to represent growth or change

Testing conditions

For each child interview: Overall Interviewer evaluation of testing conditions Type & amount of interference Child rapport w/ interviewer Attitude, motivation Physical limitations Perseverance, cooperation Language of administration

For each assessment: Interruptions or premature termination Child’s energy level Others present & their impact

Valid assessment scores for interviewed children

Assessments Completed by Children

1986 1990 1994 1998 2002 2004

PIAT Math 92.4 92.2 91.6 88.5 90.9 90.4

Reading Rec 92.0 90.6 91.3 88.5 91.1 91.2

Reading Comp 84.9 89.1 89.7 87.7 90.2 91.0

PPVT 86.9 88.0 85.2 85.8 90.4 91.0

Digit Span 90.4 89.2 94.8 89.8 93.0 92.2

SPPC 95.9 93.2 91.7 87.5 89.6 90.3

Assessments Completed by the Mother

Motor & Social 93.9 90.8 89.3 86.9 95.9 -

Temperament 95.8 96.2 94.7 92.5 96.9 97.4

The HOME 96.3 92.3 93.6 92.4 95.3 95.4

BPI 95.3 94.9 94.5 92.6 99.1 97.8

Child Age Number of Interviews 1 2 3 4 5 6 7 8 Total

All Ethnicities <1 Year 11 11

1 Year 27 27

2 Years 24 16 40

3 Years 13 62 75

4 Years 12 30 51 93

5 Years 5 20 97 122

6 Years 10 15 73 52 150

7 Years 17 12 30 146 205

8 Years 9 15 23 95 73 215

9 Years 11 20 21 38 141 231

10 Years 12 18 17 34 113 92 286

11 Years 13 15 23 21 56 203 331

12 Years 10 17 21 16 48 151 119 382

13 Years 12 11 18 15 33 94 223 40614 Years 17 6 17 24 33 53 152 135 437Total 203 257 391 441 497 593 494 135 3011

HispanicTotal 50 71 100 95 109 106 81 21 633

BlackTotal 58 56 80 104 127 158 108 29 720

Non-Black, Non-HispanicTotal 95 130 211 242 261 329 305 85 1658

Repeat Interviews: Children under age 15 as of 2004

Repeat assessments: PIATs & PPVT

Number of Valid Scores PIAT Math PIAT Reading PPVT

One valid score 1084 1077 2834

Two valid scores 1348 1449 3026

Three valid scores 1428 1411 3188

More than three valid scores 4977 4983 145

Total 8832 8820 9193

Children are counted if they had any valid score in any assessment year 1986-2004.

New in the 2006 NLSY79 Child

Mother Supplement embedded in the main Youth interview

Child Self-Administered Supplement (CSAS)

integrated into the Child Supplement (CS)

Interviewers assess children age 4-14 – no younger ages

Mothers part of “Early Bird” field effort – some children assessed later in survey year

Child Care, Family Structure, and Child Outcomes:

Possibilities for Analysis Using the Children of the NLSY79

David Blau, OSUNLS User Workshop

July 17, 2007

Introduction

• The NLSY79 and Children of the NLSY79 (CNLSY79) data are the best available resource for analyzing the determinants and consequences of child development– Sample size; overall, and by race/ethnicity– Depth and breadth of survey content– Longitudinal coverage– Intergenerational coverage– Sibling and cousin coverage

Intro - 2

• There are some limitations:– The children are not a representative sample from

a well-defined cohort– Child care data are somewhat limited– Not much information on time use or purchased

goods: it is not a time use or expenditure survey– Less information on children born to young

mothers– Not much information on absent fathers– Changes in survey design and content over time

Intro - 3

• Outline of presentation:– Brief conceptual framework– Examples of data organization and analysis from 3

papers using CNLSY79:

– The Effect of Child Care Characteristics on Child Development, David Blau, Journal of Human Resources, 34 (Autumn, 1999), pp. 786-822.

– Child Care Choices and Children’s Cognitive Achievement: The Case of Single Mothers, Raquel Bernal and Michael Keane, working paper, 2006 (http://www.faculty.econ.northwestern.edu/faculty/bernal/Bernal_Keane_IV_Single_Mothers.pdf)

– A Demographic Analysis of the Family Structure Experiences of Children in the United States, David Blau and Wilbert van der Klaauw, working paper, 2007, http://www.unc.edu/depts/econ/profs/blau/demog%20paper%20version%203.pdf

Conceptual Framework

• A “child outcome production function:”

• Sijt = 1Tijt + 2Cijt + 3Gijt + 4Xijt + µj + it + εijt , where:

– Sijt is an outcome for child i of mother j at age t (e.g., a cognitive test score)

– Tijt is a measure of cumulative maternal time input since birth

– Cijt is a measure of cumulative child care input since birth

– Gijt is a measure of cumulative goods inputs since birth

– Xijt is a set of controls for the child’s endowment and environment

– µ and δ are unobserved components of the endowment

– εijt is a transitory shock and/or measurement error

Interpretation

• Distinction between a production function and a demand equation: only proximate determinants belong in a production function

• Coefficients represent the “technology” of child development; causal effects, other things equal

• Each input could be a vector: quantity and quality; effects could vary by age; non-linear; interactions

Typical Empirical Implementation• Little information on maternal time input;

assume it equals all maternal time not spent working for pay

• Little information on goods inputs: – Use the “HOME” score as a proxy (Blau)– Substitute income for goods (Bernal & Keane)

• Other variables (X): typically mother’s education, AFQT score, age, race, ethnicity; child’s age, birth weight.

Child care data• Monthly record of child care used from birth

through age 36 months (1986, 88, 92, 94+ surveys): num. of arrangements, type, location

• Child care in the 4 weeks prior to the survey:

– type, location, payment arrangement (82-86, 88)

– group size, number and training of caregivers (85, 86, 88) [“quality”]

Does child care “quality” matter for child cognitive and behavioral development? (Blau, JHR 1999)

• Group size, num. of staff, and staff training are not very good measures of child care quality; but are often used as proxies

• Data are a snapshot of the 4 weeks prior to interview date, and were measured in only three survey years, in the 1980s

– cannot construct complete histories of quality

• Reported by the mother, not recorded by observers

• This paper uses data through 1992

Specification of child care variables

• Average quality from ages 0-2 (infant-toddler)

• Average quality from ages 3-5 (preschool)

• Other child care variables also averaged within these two age groups:– Mode, hours per week, months per year, num. of

arrangements, payment

Outcomes• Peabody Picture Vocabulary Test (PPVT), ages 3+, some

repeat assessments

• Peabody Individual Achievement Tests (PIAT) in mathematics and reading comprehension; ages 5+, repeated

• Behavior Problems Index (BPI); ages 4+, repeated

• All normed to national samples with mean 100 and SD 15

• Measured in even-number survey years, beginning in 1986

Some results

Interpretation• Consider a group of ten children cared for by one provider.

• Adding a second adult leaves GS unchanged and increases the SCR by 0.1 (from 0.1 to 0.2).

• Splitting the group in half and providing a teacher for each of the two smaller groups causes group size to fall by five and SCR to rise by 0.1.

• Based on the results in Table 4 the estimated impacts of these two hypothetical experiments are:

BPI PIAT-M PIAT-R PPVTAdd a second adult: -.00 .31 .50* .27

Split the group in half: -.40 .00 -1.35* .02

• Adding a second care giver is predicted to increase the reading score by 0.50 (3.5 percent of a SD) and to have smaller and statistically insignificant effects on the other outcomes.

• Reducing GS from ten to five while also raising SCR by 0.1 is predicted to reduce the Reading score by 1.35. These are relatively small effects in view of the large changes in GS and SCR considered in these experiments, and in the latter case the net impact is negative rather than positive.

Does child care quantity matter for child cognitive and behavioral development?

(Bernal & Keane, 2006)

• Much simpler specification of child care: cumulative time spent in child care, birth through age t

• Cumulative income as proxy for cumulative goods input

• Single mothers only

• Estimation by Instrumental variables, using state welfare waivers and welfare reform as the main source of variation in child care use: exploits geocode data

• Outcome is a combination of PPVT and PIAT math and reading test scores; includes test dummies; ages 3-6

Age profiles of maternal employment and child care use

Some results

Interpretation• Baseline specification is column (2) in Table 8.

• This model implies that each additional quarter of full-time day care reduces a child’s test score by approximately 0.70%.

• Thus, a year of full-time child care is associated with a reduction of about 2.8% in child test scores.

• This corresponds to approximately .0282/.1861 = 0.15 standard deviations of the score distribution.

• Viewed another way, a 2.8% test score reduction at age 6 would translate into about a .053 to .070 year reduction in completed schooling.

• Interpretation: this is the effect of child care time relative to the effect of mother’s time, plus the effect of any change in goods inputs that the mother may choose as a result of using day care

Family structure and child outcomes(Blau and van der Klaauw, 2007, and in progress)

• Effect of growing up in a single-parent family• Effect of family structure disruption• Effect of presence of a step-parent• Effect of living in a “blended family”• Effect of cohabitation versus marriage• And many other interesting questions

Data needed for family structure analysis

• Marital history• Cohabitation history• Pregnancy and birth history• Household roster and relationships• Child residence history• Identity of men in relation to children

NLSY79 Family Structure Data• In 1979, the survey collected information on the beginning and ending dates (to

the nearest month) of up to two marriages.

• In subsequent waves, information has been collected on up to three changes in marital status that occurred since the previous interview: marriage, separation, re-uniting after a separation, divorce, death of a spouse, and re-marriage

• Cohabitation: household roster with relationship codes, including “partner” and “other non-relative.”

• Beginning in 1990, retrospective report of the beginning date of the cohabitation, if in progress at the interview date. Also, if married at the interview date: whether cohabited before the marriage began, and begin date.

• Complete redesign of the cohabitation questions in 2002. Beginning and ending date of cohabitations that did not turn into marriages. Cohabitations that lasted less than three months are ignored.

Identifying fathers• Beginning with the 1984 interview, the mother is asked for every

biological child present in her household whether the biological father of the child is present.

• Thus, when a woman lives with a man before or during the conception or birth of a child, identifying fathers is straightforward. Cases in which a woman conceives and bears a child while single are more difficult: can identify father only if she subsequently moves in with a man.

• If she never enters a union with a man following the birth of a child, we cannot identify the child’s father.

• If she moves in with a man and the union ends before the 1984 interview, then we cannot determine the identity of the child’s father.

• If a man moves in and out between interviews, we cannot determine the father of the child.

Analysis to date

• Mainly descriptive, demographic

• Also some analysis of policy and labor market determinants of family structure

• Some descriptive statistics and illustrative results from hazard models

Conclusion• There are many interesting and useful questions about child

care, family, structure, and child outcomes that can be addressed with the CNLSY79

• It is not the ideal data set for all such questions

• But it is probably the first place to look for answers to such questions

• The most important feature of the survey: the children are being followed into adulthood => eventually, long term consequences of childhood experiences can be studied