@article{ref1,
title="A multivariate time-series approach to marital interaction",
journal="Psycho-social medicine",
year="2005",
author="Kupfer, Jörg and Brosig, Burkhard and Brahler, Elmar",
volume="2",
number="",
pages="Doc08-Doc08",
abstract="Time-series analysis (TSA) is frequently used in order to clarify complex structures of mutually interacting panel data. The method helps in understanding how the course of a dependent variable is predicted by independent time-series with no time lag, as well as by previous observations of that dependent variable (autocorrelation) and of independent variables (cross-correlation).The study analyzes the marital interaction of a married couple under clinical conditions over a period of 144 days by means of TSA. The data were collected within a course of couple therapy. The male partner was affected by a severe condition of atopic dermatitis and the woman suffered from bulimia nervosa.Each of the partners completed a mood questionnaire and a body symptom checklist. After the determination of auto- and cross-correlations between and within the parallel data sets, multivariate time-series models were specified. Mutual and individual patterns of emotional reactions explained 14% (skin) and 33% (bulimia) of the total variance in both dependent variables (adj. R(2), p<0.0001 for the multivariate models).The question was discussed whether multivariate TSA-models represent a suitable approach to the empirical exploration of clinical marital interaction.<p /><p>Language: en</p>",
language="en",
issn="1860-5214",
doi="",
url="http://dx.doi.org/"
}