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DIX
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(p
. 319
).
Sirin Socioeconomic Status and Academic Achievement
and the 1970s from that published in recent years. The first of these is the change a different aspect of SES that should be considered to be separate in the way that researchers operationalize SES. Current research is more likely to fmmthe others (Bollen, Glanville, & Stecklov, 2001; Hauser & ~ u a n g , 1997). use a diverse array of SES indicators, such Z ~ . S family income, the ~I~other's educa- Parental income as an indicator of SES reflects the potential for social and eco- tion, and a measure of family structure, rather than loolung solely at the father's nomic resources that are available to the student. The second traditional SES corn- education and/or occupation. Went, parental education, is considered one of the most stable aspects of SES
The second factor is societal change in the United States, specifically in parental because it is typically established at an early age and tends to remain the same education and family structure. During the 1990% parental education changed over time. Moreover, parental education is an indicator of parent's income dramatically in a favorable direction: Children in 2000 were living with better- because income and education are highly correlated in the United States (Hauser educated parents than children in 1980 (U.S. Department of Education, 2°00). & Warren, 1997). The third traditional SES component, occupation, is ranked on Likewise, reductions in family size were also dramatic; only about 48% of 15-to- on the basis of the education and income required to have a particular occupation 18-yex-old children lived in families with at most one sibling in 19701 as (Hauser, 1994). Occupational measures such as Duncan's Socioecono~c Index
with 73% in 1990 (Grissmer, Kirby, Berends, & Williamson, 19g4). (196 1) produce inf0Imation about the social and economic status of a household A third factor is researchers' focus on moderating factors that could influence in that they represent inf0Illlation not only about the income and education
the robust relation between SES and academic achievement (McLoyd, 1998). required for an occupation but also about the prestige and culture of a given increased attention to contextual variables such as racelethnicity, neighborhood socioeconomic stratum. characteristics, and students' grade level, current research provides a wide range A fourth indicator, home resources, is not used as commonly as the other three of information about the processes by which SES effects occur- main indicators. In recent years, however, researchers have emphasized the signif-
n u s , because of the social, economic and methodological changes that have icance of various home resources as indicators of family SES background (tole- occurred since the publication of White's (1982) review, it is difficult to estimate ha, 1988; Duncan & Brooks-Gunn, 1997; Entwisle & Astone, 1994). me$e the current state of the relation between SES and academic achievement. This qesources include household possessions such as books, computers, and a study review was designed to examine the relation between students' socioeconomicsta- feom, as well as the availability of educational services after school and in the sum- tus and their academic achievement by reviewing studies published between 1990 mm (McLo~d, 1998; Eccles, Lord, & Midgley, 1991; Entwisle & Astone). and 2000. More specifically, the goals of this review are (a) to detennine themag-
of the relation between SES and academic achievement; (b) to assess the Aggregated SES Measures
extent to which this relation is influenced by various methodological characteris- ' Education researchers also have to choose whether to use an individual stu- tics (e.g., the type of SES or academic achievement measure), and studentcharac- bent's SES or an aggregated SES based on the school that the student attends ( cd - teristics (e.g., grade level, ethnicity, and school location); and (c) to bas si Bankston, 1997) or the neighborhood where the student =sides White's meta-analysis with data from recently published studies. rooks-Gunn, Duncan, & Aber, 1997). School SES is usually measured on the
the proportion of students at each school who are eligible for reduced-price Measuring Socioeconomic Status lunch Programs at school during the school year. Students from families
~ l t h ~ ~ ~ h SES has been at the core of a very active field of research, there seems Incomes at or below 130% of the poverty level are eligible for free meals. to be an dispute about its conceptual meaning and empirical measurement with incomes between 130% and 185% of the poverty level are eligible for in studies conducted with children and adolescents (Bornstein & Bradley, 2003). d-~rice meals. Neighborhood SES, on the other hand, is usually measured
White pointed out in 1982, SES is assessed by a variety of different combina- ~ro~o*ion of neighborhood/county residents at least 20 years old who, tions ofvariables, which has created an ambiguity in interpreting research findings. ing to the census data, have not completed high school ( ~ r o ~ k ~ - ~ ~ ~ ~ , The same argument could be made today. Many researchers use SES and social ennerl &mebanov, 1995). School and neighborhood SES indicators vary in how class interchangeably, without any rationale or clarification, to refer to social and eY assess SES, but they share the underlying definition of SES as a contextual economic characteristics of students (Ensminger & Fothergill, 2003). In general dicator of social and economic well-being that goes beyond the socioeconomic terns, however, SES describes an individual's or a family's ranking on a hierar- sources available to students at home (see Brooks-Gunn, Denner, &
accorhng to access to or control over some combination of valued c~-od~- Using aggregated SES measures may introduce the issue of "ecological fallacyn ties such as wealth, power, and social status (Mueller & Parcel, 1981). to the interpretation of results from various studies with differing units of analy-
While there is disagreement about the conceptual meaning of SES, there seems The fallacy is simply a misinterpretation wherein an individual-level to be an agreement on Duncan, Featherman, and Duncan's (1972) definition of the rence is made on the basis of group aggregated data. In the context of the cur- hip&te nature of SES that incorporates parental income, parental education. and review it refers to the ~rroneous assumption that research findings at the parental occupation as the three main indicators of SES (Gottfried, 1985; Hauser, rneighborhood level also represent within-school or within-neighborhood rela- 1994; Mueller & Parcel, 1981). Many empirical studies examining the relations onships* and vice versa- Aggregated SES data on the school or neighborhood lev- among these components found moderate correlations, but more important, these be interpreted as if they represented family SES variables, nor should studies showed that the components of SES are unique and that each one measures dent-level SES data be used to explain differences between schools.
418 419
S0~~0~ConomlC Status and Academic Achievement Student characteristics Education, 1996) showed that even after accounting for family SES, there appear
~oc ioeconom~~ status is not only directly linked to academic achevement but to be a rmmber of significant differences between urban, rural, and suburban
also indirectly linked to it through multiple interacting systems, including students' schools. Data from the National Assessment of Educational Progress, for example,
racial and ethnic background, grade level, and SchooVneighborhood location indicated that the d I i ~ ~ e m e n t of children in affluent suburban schools was signif-
(Brooks-Gunn & Duncan, 1997; Bronfenbrenner & bh"Iis, 1998; Eccles, Lord, & icanfl~ and consistenfly higher than that of children in "disadvantage&' urban
Mldgley, 1991; Lemer 1991). For example, fZImily SES, which largely deter- schools (U.S. Department of Education, 2000).
mine the location of the child's neighborhood and school, not only directly In summary, the relation between SES and academic achievement was the
provides home resources but also indirectly provides "social capital," that is, sup- focus of much empirical investigation in several areas of education research in
portive among structural forces and individuals (i.e., parent-school the 1990s. Recent research employed more advanced procedures to best exam-
collaborations) that promote the sharing of societal ~~Orms and which h e the relation between SES and academic achievement. The present meta-
necessary to success in school (Coleman, 1988; Dika & Sin&, 2002). Thus analytic review was designed to assess the magnitude of the relation between
addition to the aforementioned methodological factors that likely influence SES and academic achievement in this literature. Further, it was designed to
relation between SES and academic achievement, several student characteris examine how the SES-achievement relation is moderated by (a) methodological
also are likely to influence that relation. characteristics, such as the type of SES measure, the source of SES data, and the unit of analysis; and (b) student characteristics, such as grade level, minority
Grade Level status, and school location. Finally, it was designed to determine if there has been any change in the coflelation between SES and achievement since White's 1982
The effect of and economic circumstances on academic achievement may vary by students' grade level (Duncan, Brooks-Gum, & Klebenov, 1994; Lemer~ 1991). However, the results from prior studies about the effect of grade or age on be relation between SES and academic achievement are mixed. On the one hand, Cole- Methods man et d .7s (1966) study and White's (1982) review showed that as studentSbXorne Criteria for Including Studies older, the correlation bemeen SES and school achievement diminishes. White To be included in this review, a study had to do the following: vided two possible explanations for the diminishing SES effect on academic merit. First, schools provide equalizing exp~riences, and thus the longer 1. Apply a measure of SES and academic achievement. in the schooling process, the more the impact of family SES On student achieveme 2 Report quantitative data in sufficient statistical detail for calculation of is diminished. Second, more students from lower-SES backgrounds drop out coflelations between SES and academic achievement. school, thus reducing the magnitude of the correlation. On the other handy res 3. Include in its sample students from grades kindergarten through 12, from longitudinal studies have contradicted White's results, by demonstrating that 4- Be published in a professional journal between 1990 and 2000. the gap between low- and high-SES students is most likely to remain the same sm- 5. Include in its sample students in the United States. dents get older (Duncan et al., 1994; Walker, Gree~wood, Hart, & C a 1994)7 if not widen (Pungello, Kupersmidt, Burchinal, & Patterson, 1996)- entification of Studies
Minority Status Several computer searches and manual searches were employed to gather the t~ossible pool of studies to represent the large number of existing studies on
Racial and cultural background continues to be a critical factor in academic and academic achievement. The computerized search was conducted using achievement in the United States. Recent surveys conducted by the Cen- EmC (Education Resources Information Center), PSYCINFO, and Sociolog- ter for Education Statistics (NCES) indicated that, on average, minority students Abstracts reference databases. For SES, the search terms socioeconomic lagged behind their White peers in terms of academic achievement (U.S. Depart- socio-e~onomic status, social class, social status, income, disadvantaged, merit of Education, 2000). A number of factors have been suggested to explainthe poverty were used. For academic achievement the terms achievement, lower academic achievement of minority students, but the research indicates three cess, and ~ e C b m n c e were used. The search function was created by using main factors: Minorities are more likely to live in low-income households or ins operators: "OR" was used within the SES set and the academic gle parent families; their parents are likely to have less education; and they 0 evement set of search terms, and "AND" was used between the two sets, attend under-funded schools. All of these factors are components SES cause the majority of studies used SES as a secondary or control variable and, liked to academic achievement (National Commission on Children, 19g1). eforey the computerized databases did not always index them by using one
School Location search terms as a keyword, the search was performed by using the function, not the "keyword" function. All databases were searched
l-he location of schools is closely related to the social and economic conditio 0d I990 to 2000 (on November 24, 200 1). The search yielded 1,338 of A review of research on school location (U.S. Department documents, 953 ERIC documents, and 426 Sociological Abstracts
420 421
Sirin
documents. After double entries were eliminated, there remained 2,014 unique documents.
Next, the Social Science Citation Index (SSCI) was searched for the studiesthat cited either Coleman et al.'s (1966) or White's (1982) review, or both, because both of those publications have been highly cited in the literature on SES and aca- demic achievement. Through this process, an additional 170 articles that refer- enced White's study and 266 articles that referenced Coleman's report were identified. In addition, I received 27 leads from previous narrative reviews and from studies that had been identified through the initial search. In total, the final pool contained 2,477 unique documents.
After the initial examination of the abstracts of each study, I applied the inclu- sion criteria to select 201 articles for further examination. I made the final deci- sions for inclusion after examining the full articles. Through this process, I selected 58 published journal articles that satisfied the inclusion criteria.
Coding Procedure A formal coding form was developed for the current meta-analysis on the basis
of Stocket al.'s (1982) categories, which address both substantive and methodolog- ical characteristics: Report Identification, Setting, Subjects, Methodology, Treat- ment, Process, and Effect Size. To further refine the coding scheme, a subsample of the data (k = 10) was coded independently by two doctoral candidates. Rater agree- ment for the two coders was between .80 and 1.00 with a mean of 87%. The coders subsequently met to compare their results and discuss any discrepancies between their ratings until they reached an agreement upon a final score. The coding form was further refined on the basis of the results from this initial coding procedure. The final coding form included the following components:
1. The Ident$cation section codes basic study identifiers, such as the year of publication and the names and disciplines of the authors.
2. The School Setting section describes the schools in terms of location from which the data were gathered.
3 . The Student Characteristics section codes demographic information about study participants including grade, age, gender, and racelethnicity.
4. The Methodology section gathers information about the research methcdol- ogy used in the study, including the design, statistical techniques, as well as sampling procedures.
5 . The SES and Academic Achievement section records data about SES and aca- demic achievement measures.
6. The Effect Size (ES) section codes the statistics that are needed to calculate an effect size, such as correlation coefficients, means, standard deviations, t tests, F ratios, chi-squares, and degrees of freedom on outcome measurzs used in the study.
Interrater Agreement All studies were coded by the author. A doctoral student who helped design the
coding schema coded an additional random sample of 10 studies. Interrater agree- ment levels for the six coding categories ranged from 89% for the methodology - - - - - - -
section to 100% for the names of the coding form.
Analytical Procedures Calculating Average Effect Sizes
The effect size (ES) used in this review was Pearson's correlation coeflcient r. Because most results were reported as a correlation (k = 4 3 , the raw correlation coefficient was entered as the ES measure. There were 8 studies that did not orig- inally report correlations but provided enough information to calculate correlations usiig the formulas taken from Hedges and Olkin (1985), Rosenthal(1991), and Wolf (1986) to convert the study statistic to r. Correlations oversestimate the pop- ulation effect size because they are bounded at -1 or 1. As the correlation coeffi- cients approach -1 or 1, the distribution becomes more skewed. To address this problem, the correlations were converted into Fisher's Z score and weighted by the inverse of the variance to give greater weight to larger samples than smaller sarn- ples (Lipsey & Wilson, 2001). The average ESs were then obtained through a z-to-r transformation with confidence intervals to indicate the range within which the population mean was likely to fall in the observed data (Hedges & Olkin). The confidence interval for a mean ES is based on the standard error of the mean and a critical value from the z distribution (e.g., 1.96 for a = .05).
Statistical Independence There are two main altemative choices for the unit of analysis in meta-analysis
(Glass, McGaw, &Smith, 198 1). The first altemative is to use each study as the unit of analysis. The second approach is to treat each correlation as the unit of analysis. Both of these approaches have shortcomings. The former approach obscures legitimate dif- ferences across multiple comelations (i.e., the correlaaon for minority students versus the correlation for White students), while the latter approach gives too much weight to those studies that have multiple correlations (Lipsey & Wilson, 2001). A third alterna- tive, which was chosen for this study, is to use "a shifting unit of analysis" (Cooper, 1998). This approach retains most of the information from each study while avoiding any violations of statistical independence. According to this procedure, the average effect size was calculated by using the first alternative; that is, one correlation was selected from each independent sample. The same procedure was followed when the
, focus of analysis was a student characteristic (e.g., minority status, grade level, or f school location). For example, d a study provlded one correlation for White students
and another for Black students, the two were included as independent correlations in I the same analysis. The only exception to this rule was the moderation tests for the r methodological characteristic (e.g., the types of SES or academic achievement mea- t sure). For example, if a study provided one correlation based on parental education and 1 another based on parental occupation, they were both entered only when the modera- 1 tor analysis was for the type of SES measure. In both alternatives, there was only one 1 correlation from each study for each construct. When studies provided multiple corre- I lations for each subsample, or multiple correlations for each construct, they were aver- / aged so that the sample on which they were based contributed only one correlation to I any given analysis. Thus, in Tables 1 (page 424) and 2 (page 429), the correlation for
each study is the average correlation (r) for all constructs for that specific sample.
Fixed and Random Effects Models There is an ongoing discussion about whether one should use a fixed or random
effects model in meta-analysis (Cooper & Hedges, 1994; Hedges & Vevea, 1998).
TA
BL
E 1
Su
mm
ary
of th
e in
depe
nden
t sam
ples
Aut
hor(
s)
Gra
de/
Eth
nici
ty
Scho
ol
SE
S
Ach
ieve
men
t N
of
stud
ents
(p
ublic
atio
n ye
ar)
scho
ol le
vel
(or %
min
ority
) lo
catio
n m
easu
re
mea
sure
(o
r N o
f sc
hool
s)
r
Ale
xand
er, E
ntw
isle
, Pr
imar
y 60
B
altim
ore
FRLa
GPA
45
3 ,3
91
& B
edin
ger (
1994
);
scho
ols
Edu
catio
n A
chie
vem
ent T
est
489
Ent
wis
le, A
lexa
nder
, &
Ols
on (1
994)
A
lspa
ugh
(199
1);
Prim
ary
N/A
U
rban
/mra
l %
FR
L
Mis
sour
i Mas
tery
U
rban
sch
ool
Urb
an =
A
lspa
ugh
(199
2)
Ach
ieve
men
t Tes
t N
= 3
9 .7
19
Rur
al s
choo
l R
ural
=
Bal
li, D
emo,
&
Wed
man
(199
8)
Bro
wn
et a
l. (1
993)
Cal
das &
Ban
ksto
n (1
999)
; Cal
das
(199
3)
Cal
das &
Ban
ksto
n (1
999)
; Ban
ksto
n &
Cal
das
(199
8)
Car
lson
et a
l. (1
999)
Che
n, L
ee, &
St
even
son
(199
6)
Mid
dle
Mea
n ag
e 9.
5 ye
ars
Gra
des
K-1
2
Gra
de 1
0
Gra
des
1-3
Hig
h sc
hool
Whi
te
Mid
wes
tern
sc
hool
N
IA
NIA
44
Lou
isia
na
publ
ic
scho
ols
Bla
ck a
nd
Lou
isia
na
Whi
te
publ
ic
scho
ols
17
Min
neap
olis
N/A
M
inne
apol
is
met
ropo
litan
ar
ea
Inco
me
Hol
lings
head
(1
975)
%FRL
Inco
mea
E
duca
tion
Scho
ol
Dun
can'
s SE
Ib
Inco
me
Edu
catio
n E
duca
tiona
O
ccup
atio
n H
ome
Ach
ieve
men
t T
est
K-A
BC
A
chie
vem
ent
Com
posi
te
Ach
ieve
men
t T
est
Ach
ieve
men
t Tes
t
Mat
h an
d ge
nera
l in
form
atio
n te
sts
N =
106
74
26
Scho
ol
N=
1,3
01
W =
21,
263
B =
13,
279
168
213
Chr
istia
n, M
orri
son,
K
inde
rgar
ten
& B
ryan
t (19
98)
Dix
on-F
loyd
&
Gra
des
68
Jo
hnso
n (1
997)
Dor
nbus
ch, R
itter
, H
igh
scho
ol
& S
tein
berg
(1
991)
Feln
er a
t al.
(199
5)
Gra
des
7-9
Gon
zale
s, C
auce
, G
rade
s 7-
8 Fr
iedm
an, &
M
ason
(199
6)
Gre
enbe
rg, L
anga
u,
Gra
de 1
C
oie,
&
Pind
erhu
ghes
(1
999)
Gri
ffith
(199
7)
Gra
des
3-6
Gro
lnic
k &
G
rade
s 6
8
Slow
iacz
ek
(1 99
4)
Bla
ck a
nd
Whi
te
49
Bla
ck
47
Gre
ensb
oro,
NC
E
duca
tion
El P
aso,
'IX
, FRL
scho
ol d
istr
icts
Subu
rban
E
duca
tiona
N
eigh
borh
ood
Bla
ck-U
rban
E
duca
tion
Whi
te-M
ixed
Rur
al S
outh
east
H
ollin
gshe
ad's
(1
975)
fo
ur-f
acto
r U
rban
E
duca
tion
a
Inco
me
Nei
ghbo
rhoo
d N
atio
nwid
e E
duca
tion
a
mul
ti-st
ate
Occ
upat
ion
long
itudi
nal
Hom
e st
udy
Nei
ghbo
rhoo
d
Subu
rban
%
FR
L
scho
ol
dist
rict
N
IA
Edu
catio
n
Tex
as A
sses
smen
t fo
r A
cade
mic
Sc
ores
Se
lf-r
epor
ted
GPA
Self
-rep
orte
d G
PA
CA
T
GPA
GPA
12
0 .1
3@
Woo
dcoc
k-Jo
hnso
n 33
7 ,2
49
Psyc
ho-
Edu
catio
nal
Bat
tery
- R
evis
ed
Cri
teri
on
Scho
ol
.650
R
efer
ence
d N
= 1
19
Tes
t G
PA
302
,095
(con
tinue
d)
TA
BL
E 1
(Con
tinue
d)
Q\
Aut
hor(
s)
Gra
de1
Eth
nici
ty
Scho
ol
SE
S
Ach
ieve
men
t N
of
stud
ents
(p
ublic
atio
n ye
ar)
scho
ol le
vel
(or %
min
ority
) lo
catio
n m
easu
re
mea
sure
(o
r N o
f sc
hool
s)
r
Gul
lo &
Bur
ton
Kin
derg
arte
n 21
U
rban
FRL
Met
ropo
litan
1,
573
.124
(1
993)
R
eadi
ness
Tes
t (N
urss
&
McG
auvr
an,
1974
) Ji
mer
son,
G
rade
1
36
Urb
an
Dun
can'
s SE
Ib
Ach
ieve
men
t 14
3 .3
00
Ege
land
, E
duca
tion
Tes
t Sr
oufe
, &
Occ
upat
ion
Car
lson
(200
0)
Inco
me
John
son
& L
indb
lad
Gra
de 6
33
E
aste
rn c
ity
FRL
SRA
Ass
essm
ent
1,68
6 .I
75
(199
1)
Surv
ey
Ken
nedy
(19
92)
Prim
ary
Bla
ck a
nd
Mix
ed
Edu
catio
nb
Ach
ieve
men
t W
M =
1,3
28
WM
=
scho
ol
Whi
te
Occ
upat
ion
Tes
t B
M =
1,0
28
.330
B
M =
.I60
Klin
gele
&
Gra
de 4
19
W
arri
ck (1
990)
A
rkan
sas
%F
RL
sc
hool
di
stri
cts
Bal
timor
e %
FR
L
scho
ols
MA
T-6
Sc
hool
.5
4 N
=3
32
% o
f st
uden
ts
Scho
ol
.73
abov
e m
edia
n N
=9
7
CA
T s
core
s A
chie
vem
ent T
est
1,20
0 .3
15
GPA
69
6 .I
80
Lar
ndin
(19
96)
Gra
des
79
K-1
2
Mix
ed
Edu
catio
n H
awai
ian
Edu
catio
n M
cDer
mot
t (19
95)
Mix
ed
3 1
Miy
arno
to e
t al.
Gra
des
76
(2c"
30)
9-1
2 O
'Bri
en,
Gra
de 1
1 60
M
artin
ez-P
ons,
Pr
e-Sc
hola
stic
41
5 .I
50
Apt
itude
Tes
t L
arge
In
com
e m
etro
polit
an
& K
opal
a (1
999)
O
tto &
Atk
inso
n G
rade
11
28
area
N
orth
Car
olin
a E
duca
tiona
C
AT
(1
997)
ru
ral c
ount
ies
Occ
upat
ion
Ove
rstr
eet,
Hol
mes
, D
unla
p, &
Fre
ntz
(1 99
7)
Patte
rson
, K
uper
smid
t, &
V
aden
(199
0);
Pung
ello
, K
uper
smid
t, B
urch
inal
, &
Patte
rson
(1 99
6)
Rec
h &
Ste
vens
( 1
996)
R
ippl
e &
Lut
har
(200
0).
Schu
ltz (1
993)
Age
8-1
6
year
s 50
N
IA
Hol
lings
head
(1
975)
W
RA
T -R
11
6 .6
21
Gra
des
2-4
38
Urb
an
Publ
ic
Ass
ista
nce
SRA
Ach
ieve
men
t M
= 4
1 7
M =
.409
T
est
F=
45
1
F =
.391
Gra
de 4
Gra
de 9
Gra
des 46
Gra
des 46
Bla
ck
Urb
an
FRL
CA
T
85
Urb
an
Hol
lings
head
tw
o-fa
ctor
B
lack
and
U
rban
FR
L
His
pani
c 96
Su
burb
an n
ear
Edu
catio
nb
larg
e In
com
e M
idw
est
city
6
Mar
ion
FRL
Cou
nty,
WV
19
N
IA
Occ
upat
ion
GPA
BA
SIS
Seyf
ried
(199
8)
GPA
M
AT
Shav
er &
Wal
ls
(1 99
8)
Stra
ssbu
rger
, R
osen
, Mill
er,
8~ C
have
z (1
990)
Su
tton
& S
oder
stro
m
(1 99
9)
Tho
mps
on e
t al.
(199
2)
Gra
des
7-8
Gra
des
7-9
CT
BS
GPA
Gra
des
3 an
d 10
M
ixed
27
Mix
ed
FRL
A
chie
vem
ent
Tes
t A
chie
vem
ent
Tes
t
Scho
ol
N =
2,3
07
76
NIA
N
IA
Hol
lings
head
tw
o-fa
ctor
(1
957)
(c
ontin
ued)
