The present research studies marital dissolution using data from both spouses from the National Survey of Families and Households (NSFH) and uses the method of multiple imputation to handle missing data. Role theory and another four approaches (social exchange theory, stake theory, gender perspective and heterogeneity perspective) are used to make a methodological argument why using data from both spouses is necessary to study marital stability. Five data sets are imputed and there are 3,777 observations in each imputed data set. Main research findings are as followed. First, the model fits of the data from both spouses on marital dissolution are significantly better than the model fits of the data from one spouse only; therefore, gathering perceptual data from both spouses is necessary to understand marital dissolution. Second, overall, the effects of most spousal discrepancies do not support the heterogeneity perspective. Third, the model fits of the wife only model are significantly better than the model fits of the husband only model across different periods of marital duration, and the predictability of wives' variables is more stable than husbands' variables. Therefore, if only individual-level data are available to use, researchers are encouraged to use wives' data rather than husbands' data. Fourth, the predictability of factors varies with marital duration and gender in the models with data from both spouses.
College and Department
Family, Home, and Social Sciences; Sociology
BYU ScholarsArchive Citation
Lu, Chao-Chin, "Predicting Marital Dissolution Using Data from Both Spouses" (2010). Theses and Dissertations. 2853.
marital dissolution, divorce, separation, multiple imputation, data from both spouses, dyadic couple data, role theory, stake theory