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Beyond Access: Digital divide, Internet Use and Gratifications Gained
Unformatted Document Text:  R ETHINKING THE D IGITAL D IVIDE 11 gained. Then, we attempted to see whether the patterns of relationship between Internet use and gratification gained are different depending on socio-economic status and age, the two most important individual level factors in the presistent digital divide. Socio-economic status was constructed by combining income and education, both of which were standardized from 0 to 1. Socio-economic status and age were dichotomized at the median value. These two dichotomies create four subgroups: the high SES-young (N=457), the high SES-old (N=602), the low SES- young (N=675), and the low SES-old (N=439). Due to moderate correlation between socio- economic status and age, sample sizes in these four subgroups are not equal. Then, structural equation modeling techniques were applied again to all four subgroups. Taken as a whole, this study presents five path models: one whole sample model and four subgroup models. In order to rule out potential confounding variables, we employed a residualized covariance matrix as input. To construct the residualized matrix, the six variables of our interest, Internet use and gratifications, were regressed onto the sets of control variables. These regressions produce residuals, the part not explained by the controls, with which we construct covariance matrix to be analyzed. In so doing, we can except that our model would be controlling for the variables used to create the residuals. We report outputs of the regression analyses in order to note how much variances in the Internet use and gratification variables of our interest were explained by the control variables (see Table 1-5). Since the variances explained by a set of control variables were already taken out by using residualizing technique, the total variances reported in the following path models can be interpreted as amount of variances uniquely explained by types of Internet use.

Authors: Cho, Jaeho., Zuniga, Homero Gil de., Nah, Seungahn., Humane, Abhiyan., Hwang, Hyunseo., Rojas, Hernando. and Shah, Dhavan.
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background image
R
ETHINKING THE
D
IGITAL
D
IVIDE
11
gained. Then, we attempted to see whether the patterns of relationship between Internet use and
gratification gained are different depending on socio-economic status and age, the two most
important individual level factors in the presistent digital divide. Socio-economic status was
constructed by combining income and education, both of which were standardized from 0 to 1.
Socio-economic status and age were dichotomized at the median value. These two dichotomies
create four subgroups: the high SES-young (N=457), the high SES-old (N=602), the low SES-
young (N=675), and the low SES-old (N=439). Due to moderate correlation between socio-
economic status and age, sample sizes in these four subgroups are not equal. Then, structural
equation modeling techniques were applied again to all four subgroups. Taken as a whole, this
study presents five path models: one whole sample model and four subgroup models.
In order to rule out potential confounding variables, we employed a residualized covariance
matrix as input. To construct the residualized matrix, the six variables of our interest, Internet use
and gratifications, were regressed onto the sets of control variables. These regressions produce
residuals, the part not explained by the controls, with which we construct covariance matrix to be
analyzed. In so doing, we can except that our model would be controlling for the variables used to
create the residuals. We report outputs of the regression analyses in order to note how much
variances in the Internet use and gratification variables of our interest were explained by the
control variables (see Table 1-5). Since the variances explained by a set of control variables were
already taken out by using residualizing technique, the total variances reported in the following
path models can be interpreted as amount of variances uniquely explained by types of Internet use.


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