Marital Satisfaction – Interpreting Research Questions Using ANOVA

For the article “Marital Satisfaction Over the Family Life Circle”, the independent variables are two: The Blood and Wolfe and the Rollins and Feldman assessment methods (Rollins & Feldman, 1970). The dependent variable is the Locke-Wallace instrument; this instrument is used to measure marital satisfaction for a number of different couples.  The main purpose of the study was to examine discrepancies in earlier studies between the pattern of marital satisfaction following the “schoolage” stage of the family life cycle for wives and husbands over the whole life cycle. The total number of variables examined in the analysis is three; the article used one-way ANOVA analysis (Shadish et al., 2003). The authors report an F-score of 5.43 for the relationship of life cycle (independent variable) on marital satisfaction (dependent variable); this score was significant at the .01 level.

Overall, the article found that there is a changing and declining relationship between the wife and husband over time starting with the birth of children and continuing on through the trajectory of the child’s life. This is a typically used study methodology (Shuttleworth, 2008).

The second article selected is: “Effects of Demographic Variables on Marriage Satisfaction.” (Zaniah et al, 2012). The article’s main research question is to explore which demographic variables predict marriage satisfaction in an Asian population. In this study, the dependent variable is marriage satisfaction measured by the ENRICH Marital Satisfaction Scale. The independent variables are all demographic variables that include length of marriage and income.  The data was analyzed using basic t-tests and one-way ANOVA statistical analysis. The authors initially conducted a t-test to assess the difference in marital satisfaction (independent variable) based on marriage length (dependent variable). The t-test showed a mean score of 56.14 for those couples that were married more than 10 years; the t-test showed a mean score of 52.24 for those couples married less than 10 years, with a p-value less than .05 (p<.05).

For the one-way ANOVA with the independent variable (income) and dependent variable (marital satisfaction) the F statistic was 5.848, a p-value roughly equivalent to .01. The authors also conducted a one-way ANOVA with spouse’s income (independent variable) on marital satisfaction; the analysis produced an F-Score of 3.947 with a p-value less than .05 (p<.05).  The study found significant differences in marital satisfaction based on income and marriage length: the variables length of marriage and marital satisfaction were positively correlated; the variables income and marriage length were also positively correlated.  Overall, this study was interesting in that it used basic demographic variables in order to predict marital satisfaction.  I would like to include basic demographic variables in my model in order to replicate these results and build a base for understanding other relationships.


Rollins, B. C., & Feldman, H. (1970, February). Marital Satisfaction over the Family Life Cycle. Journal of Marriage and Family, 32(1), 20-28. Retrieved from

Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. New York: Houghton Mifflin Company.

Shuttleworth, M. (2008a). Quasi-Experimental Design. Retrieved from Explorable:

Zaniah, A.Z., Nasir, R., Ruzy, S.H. & Yusof, N.M.  (2012). Effects of Demographic Variables on Marital Satisfaction. Asian Social Science, 8(9), 46-49. Retrieved from: Asian Social Science Journal.