Sentences with phrase «dyadic analysis»

Using dyadic analysis in health psychology.

Marital quality and loneliness in later life: A dyadic analysis of older married couples in Ireland.

Structural equation modeling was used to conduct dyadic analyses on the variables.

With respect to the dyadic analyses, we hypothesized socialization effects of alcohol misuse across different stable dyadic relationships, both unilateral and reciprocal.

Social network and dyadic analyses were applied in a complementary manner to estimate peer socialization effects across the different friendship contexts.

Not exact matches

As described in the main text, ordered logistic regression analyses were carried out for each brain region in which social network distances were modeled as a function of local neural response similarities and dyadic dissimilarities in control variables (gender, ethnicity, nationality, age, and handedness).

To gain insight into what brain regions may be driving the relationship between social distance and overall neural similarity, we performed ordered logistic regression analyses analogous to those described above independently for each of the 80 ROIs, again using cluster - robust standard errors to account for dyadic dependencies in the data.

Using Social Relations Model analyses, we examined evolutionarily informed hypotheses on both individual and dyadic effects of participants» physical characteristics, personality, education and income on their dating, mating and relating.

An analysis of dyadic interactions of approximately 65,000 heterosexual users of an online dating system in the U.S. showed that, despite these differences, users of the system sought people like them much more often than chance would predict, just as in the offline world.

105 David A. Kenny et al., Dyadic Data Analysis 78 — 79 (2006).

His work includes the application of cross-spectral analysis and bootstrapping methods to dyadic sexual desire data.

Day - to - day changes in intimacy predict heightened relationship passion, sexual occurrence, and sexual satisfaction: A dyadic diary analysis.

Dyadic data analyses in a developmental context.

Development and validation of a brief version of the Dyadic Adjustment Scale with a nonparametric item analysis model.

Dyadic data analyses also revealed that when prosocial behavior was low, aggression was negatively

Because the data were dyadic (i.e., data from both members of the pair), mean couple scores were created for each variable, and these couple mean scores were used in the analyses below.

A longitudinal test of a developmental framework for the analysis for premarital dyadic formation.

Dyadic data analyses also revealed that when prosocial behavior was low, aggression was negatively... related to friendship quality.

[book] Kenny, D. A. / 2009 / Dyadic data analysis using multilevel modeling, In The handbook of multilevel analysis / Taylor Francis

Although the current study has a number of important strengths, such as the observational design, the comparison of AD and non-AD children, the examination of real - time dyadic emotions using innovative state space grid analyses, and the inclusion of father - child and mother - child dyads, several limitations should also be noted and addressed in future research.

Since we were interested in the specific effects of paternal and maternal AD on the dyadic emotional processes during interactions, analyses were performed separately for father - child and mother - child interactions.

Measures of dyadic emotional expressivity (positive and negative affect) and dyadic emotional flexibility (transitions, dispersion, average duration) were derived from these interactions using state space grid analysis.

Dyadic data analysis with structural equation modeling is used to determine the respective contributions of each respondent's predictors (i.e., actor effects) and his / her spouse's or partner's predictors (i.e., partner effects).

Furthermore, by performing APIM analyses (Olsen & Kenny, 2006), we more optimally utilized the dyadic nature of these peer interactions.

The collection and analysis of dyadic data present additional complexities compared to the study of individuals.

Follow - up analyses examining specific subscales of observed dyadic coping (see Table 6) indicated that nondistressed couples with a depressed wife (G2) demonstrated significantly higher values in relative duration (F (3, 58) = 2.80, p ≤ 0.05) and frequency (F (3, 58) = 2.73, p ≤ 0.05) of problem focused stress communication, although this comparison was only significant in comparison to distressed couples with a depressed husband (G3).

Grid - sequence analysis, by explicitly creating and working with the dyad - level time series, may provide for identification of distinct patterns of dyadic function that are related to overall function.

In this initial demonstration, we apply grid - sequence analysis to dyadic experience sampling data obtained in a study of older couples» daily lives.

In particular, as a new method for the analysis of dyadic experience sampling data, we suggest that grid - sequence analysis will help identify new typologies of dyad - level microdynamics that indicate risk or protective factors that are useful for intervention efforts.

Topics to be addressed include the measurement of nonindependence, the Actor - Partner Interdependence Model, the analysis of distinguishable and indistinguishable dyads, and the analysis of over-time dyadic data (e.g., dyadic growth curve models).

Using dyadic data from 108 older couples (MAge = 75.18 years) with six within - day emotion and activity reports over 7 days, we illustrate how grid - sequence analysis can be used to identify a taxonomy of dyads with different emotion dynamics.

Using grid - sequence analysis, we found that clusters with different intradyad dynamics also differ on both men's and women's dyadic adjustment (as indicated by perceptions of agreement on amount of time spent with partner) and on men's subjective health.

This general approach — to first quantify the intradyad relationships and then examine interdyad differences in the intradyad relationships — is the basis for most contemporary dyadic data analysis techniques, including sequential and state space grid analyses, coupled dynamic systems, and multilevel modeling (Bakeman & Gottman, 1997; Bakeman & Quera, 2011; Boker & Laurenceau, 2007; Gonzalez & Griffin, 2012; Gottman, Murray, Swanson, Tyson, & Swanson, 2002; Hollenstein, 2013; Laurenceau & Bolger, 2005; Ram & Pedersen, 2008).