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PARENTAL INVOLVMENT, FAMILY STRUCTURE, AND ACADEMIC ACHIEVEMENT - page 30 / 102

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involved pre-adolescent students aged five to nine, it is consistent with the larger body of

research which supports a link between SES and academic achievement. It is also

different in the number of SES variables that were used to evaluate SES. In the Crane

study, the eight factors that were used to operationalize SES include family income,

mother’s education, father’s education, mother’s occupational status, father’s

occupational status, household size, marital status, and the percentage of students at the

mother’s high school who were poor (p.308).

The results of Crane’s research demonstrate a clear link between mathematics test

scores and income, although the “effects of the SES variables were smaller than those of

home environment” (1996:309). In addition, the SES variable in Crane’s study was not

operationalized in composite form. Crane’s research yields coefficients for each

component of SES individually. For example, an increase of one standard deviation in

family income ($10,600) raised mathematics scores by 2.9 percentiles (p.309). In the

Attewell and Battle study, coefficients for the effect of having a home computer on

academic achievement indicate a statistically significant, positive relationship, but

“computer effects on test scores are markedly smaller after controlling for SES”

(1999: 4).

In other studies, the unit of analysis is the aggregate SES of students at the school or

the neighborhood SES, based on location of the school. The components used to evaluate

school or neighborhood SES are similar, yet they do vary in some aspects. For example,

in a study designed to evaluate the effect of SES on public high school rankings and

outcomes, Toutkoushian and Curtis (2005) selected unemployment rate for the school

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