arXiv subjects

Fiona Steele

Publications and source records attributed to Fiona Steele.

4 recordsLinked to original sources

arXiv2026

Multilevel modelling of double-sampled clustered social networks with individual-level data on between-cluster ties

We consider the analysis of dyadic network data on ties between individuals in different clusters where the presence of a directed tie is reported by each individual in a dyad and the cluster-level network is of interest. A generalisation of the Social Relations Model (SRM) is proposed which includes actor, partner and dyad effects at the individual and cluster levels. The model additionally uses ``double-sampling'' of ties to estimate a measurement model which adjusts for and quantifies the extent of reporter effects. The model can be viewed as a type of multilevel structural equation model, with multiple cross-classified random effects, which can be estimated using Markov chain Monte Carlo (MCMC) methods in Bayesian software. Using parameter estimates from this multilevel SRM, we then propose two alternative ways of deriving the between-cluster network that are based on predictions of the strength of between-cluster ties. Our approach is illustrated using data on social support networks in a rural community in Nicaragua where individual reports of bidirectional exchanges of support with individuals from other households are used to derive the between-household network.

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arXiv2022

Longitudinal analysis of exchanges of support between parents and children in the UK

We consider how exchanges of support between parents and adult children vary by demographic and socio-economic characteristics and examine evidence for reciprocity in transfers and substitution between practical and financial support. Using data from the UK Household Longitudinal Study 2011-19, repeated measures of help given and received are analysed jointly using multivariate random effects probit models. Exchanges are considered from both a child and parent perspective. In the latter case, we propose a novel approach to account for correlation between mother and father reports and develop an efficient MCMC algorithm suitable for large datasets with multiple outcomes.

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arXiv2022

Modelling Correlation Matrices in Multivariate Dyadic Data: Latent Variable Models for Intergenerational Exchanges of Family Support

We define a model for the joint distribution of multiple continuous latent variables which includes a model for how their correlations depend on explanatory variables. This is motivated by and applied to social scientific research questions in the analysis of intergenerational help and support within families, where the correlations describe reciprocity of help between generations and complementarity of different kinds of help. We propose an MCMC procedure for estimating the model which maintains the positive definiteness of the implied correlation matrices, and describe theoretical results which justify this approach and facilitate efficient implementation of it. The model is applied to data from the UK Household Longitudinal Study to analyse exchanges of practical and financial support between adult individuals and their non-coresident parents.

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arXiv2021

Latent variable models for multivariate dyadic data with zero inflation: Analysis of intergenerational exchanges of family support

Understanding the help and support that is exchanged between family members of different generations is of increasing importance, with research questions in sociology and social policy focusing on both predictors of the levels of help given and received, and on reciprocity between them. We propose general latent variable models for analysing such data, when helping tendencies in each direction are measured by multiple binary indicators of specific types of help. The model combines two continuous latent variables, which represent the helping tendencies, with two binary latent class variables which allow for high proportions of responses where no help of any kind is given or received. This defines a multivariate version of a zero inflation model. The main part of the models is estimated using MCMC methods, with a bespoke data augmentation algorithm. We apply the models to analyse exchanges of help between adult individuals and their non-coresident parents, using survey data from the UK Household Longitudinal Study.

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