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Meta-Analysis Of Studies Investigating The Effects Of Father Absence On Children'S Cognitive Development

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The purpose of the present study was the integration of the father-absence research to determine the effects of father absence on children's cognitive development as assessed by standardized intelligence, aptitude, and achievement tests and school grades. The study used the quantitative integrative review methodology of meta-analysis through which the findings from individual studies were integrated and relations between the study findings and characteristics were explored. The meta-analytic approach involved transforming the findings of individual studies to a common metric (i.e., effect size), describing and coding the characteristics of the studies, and then using the analysis of variance and multiple regression analysis to determine whether there were overall effects, subsample effects, and relations among the characteristics of the studies and the study findings. Extensive manual and computer searches uncovered 137 father-absence studies representing 9,955,118 father-absent and father-present subjects from preschool to college age. Analysis of the study findings at the highest level of aggregation yielded a mean effect size of -.26 reflecting a .26 standard deviation superiority of the father-present subjects over the father-absent subjects. Mean effect sizes were found to differ significantly as a function of age of the child at onset of the father absence, age of the subjects at time of study, sample size, sample geographic distribution, and number of matched/controlled factors in each study. Five significant correlations between study characteristics and study effect sizes were obtained: (1) larger effect sizes were associated with father-absence onset during 7-12 years of age; (2) larger effect sizes were identified with younger study subjects; (3) larger effect sizes were associated with smaller study sample sizes; (4) larger effect sizes were related to narrow geographic distributions of study samples; and (5) larger effect sizes were associated with a greater number of matched or controlled factors in the study. Only 14% of the total variance in the study effect sizes was accounted for by the composite set of predictors (i.e., study characteristics).

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