those with a University degree do not have statistically significant different social network size from those completing only primary school. As such, the evidence suggests tentatively that having a poorer or higher than secondary education may be related with poorer social network size. However, there is no evidence that increased age and social network size decline leads to decreased social participation. These findings are inconsistent with the arguments of Cummings and Henry (1961) who advocated the manifestation of social withdrawal in older age, with the loss of social ties to be a plausible explanation for a reduction in social participation. The relevant evidence points to increased income influencing social one’s participation frequency positively, suggesting that it may help in retaining social participation in the face of social ties losses with age. In relation to Internet use, the predictive ability of age may reflect a cohort effect, namely that older cohorts have lower rates of Internet use than younger generations. These findings are consistent with evidence depicting that globally, older adults have the lowest percentages of Internet use compared to all other age groups (Zickhur and Madden, 2012). The evidence however also depicts that being an older woman in Greece predicts even less Internet use. The evidence deriving from the regression analyses in this chapter should be taken under consideration with extreme caution. As the model in total explained a variance between .171 and .270, the inclusion of 3 to 4 predictors with the sample size available (N = 92) does not offer enough statistical power for a good prediction level (Knofczynski & Mundfrom, 2017). As such, the risk of having produced a type II error has been comparatively higher in these analyses. Conclusion
those with a University degree do not have statistically significant different social network size from those completing only primary school. As such, the evidence suggests tentatively that having a poorer or higher than secondary education may be related with poorer social network size. However, there is no evidence that increased age and social network size decline leads to decreased social participation. These findings are inconsistent with the arguments of Cummings and Henry (1961) who advocated the manifestation of social withdrawal in older age, with the loss of social ties to be a plausible explanation for a reduction in social participation. The relevant evidence points to increased income influencing one’s social participation frequency positively, suggesting that it may help in retaining social participation in the face of social ties losses with age. In relation to Internet use, the predictive ability of age may reflect a cohort effect, namely that older cohorts have lower rates of Internet use than younger generations. These findings are consistent with evidence depicting that globally, older adults have the lowest percentages of Internet use compared to all other age groups (Zickhur and Madden, 2012). The evidence however also depicts that being an older woman in Greece predicts even less Internet use. The evidence deriving from the regression analyses in this chapter should be taken under consideration with extreme caution. As the model in total explained a variance between .171 and .270, the inclusion of 3 to 4 predictors with the sample size available (N = 92) does not offer enough statistical power for a good prediction level (Knofczynski & Mundfrom, 2017). As such, the risk of having produced a type II error has been comparatively higher in these analyses. Conclusion
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