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The overall purpose of this study was to test claims regarding both the efficacy and mechanism of change for Emotion Focused Couple Therapy (EFT). Although a number of treatment outcome studies have been conducted on EFT, the vast majority of these studies emanate from the research laboratories associated with the two founders of EFT. Additionally, most EFT research has examined treatment outcome rather than mechanisms of change. This study used a time-series single-case experimental design approach to examine both the efficacy and the mechanisms of change in EFT for couple distress. I systematically tracked the symptoms of couple distress across the span of an EFT treatment and explored how symptom severity varied over time within the dyad across several measures. Simulation modeling analysis (SMA) for time-series data was used to evaluate the level change across baseline, treatment, and follow-up phases. Further, crosslag correlational analyses were used to clarify the mechanism of change in EFT. Experimental results from the time-series design provided moderate support for the EFT efficacy claim. Partial support was also found for the underlying EFT mechanism of action claim linking attachment insecurity and marital distress. Two of the EFT mechanism of action claims and an interpersonal mindfulness exploratory hypothesis, however, were unsupported by the experimental data. Implications for future research are discussed.

Sophisticated Bayesian methods are often used to identify a collection of allelesthat are jointly associated with a particular disease. A disease might not beexpressed when only one of these alleles is present, but each associated allelemight interact with each other in a rather complicated way, causing a disease tobe expressed. In investigating a patient's susceptibility to a disease, it is oftenuseful to group the collection of associated alleles according to their risk factors.Our goal is to find the most likely grouping structure of alleles associated with Rheumatoid Arthritis given a case-control data. The numberof ways to group these m alleles is given by the mth Bell number Bm. For 10 alleles, thistranslates to 115,975 groupings. For m = 15, we have over a billion ways to groupthe alleles. Clearly computing the probability for each grouping soon becomeintractable. A combination of Metropolis-Hastings and local search algorithm isproposed to accomplish this task. This strategy is first implemented on simulateddata, with a sufficiently large sample size and a known grouping structure, andthe correct grouping is obtained. Stable results are obtained as the algorithm isrun multiple times on Rheumatoid Arthritis data.

2031-01-02