Abstract:The growing popularity of life course research has given rise to an increasing number of methodological and statistical techniques that incorporate life course elements of events, timing, duration stages, and sequencing. The primary objective of this article is to advance dynamic family theories through methodological improvement in the form of optimal matching analysis (OMA). OMA has been growing in popularity as a method for studying
“…Although Rodgers () predicted that stochastic modeling would be the future of development theory, referring specifically to the “game tree” analysis illustrated by Magrabi and Marshall (), White () had the advantage of almost 20 years of computational advancement when he demonstrated the potential of Rodgers's prediction. Similarly, Martin () benefited from another 20 years of advancement when he further demonstrated newer statistical techniques to test the complex propositions of development theory. In an overview of the general state of family theory, White () stated: It seems, however, the awareness of levels of analysis and the methodological and statistical advances we have experiences in the last few decades have “out paced” theoretical developments and our understanding of what is involved in constructing multilevel theories with cross‐level interaction.…”
Section: Methodological Limitationsmentioning
confidence: 99%
“…Although Rodgers (1973) predicted that stochastic modeling would be the future of development theory, referring specifically to the "game tree" analysis illustrated by Magrabi and Marshall (1965), White (1991) had the advantage of almost 20 years of computational advancement when he demonstrated the potential of Rodgers's prediction. Similarly, Martin (2015) benefited from another 20 years of advancement when he further demonstrated newer statistical techniques to test the complex propositions of development theory. In an overview of the general state of family theory, White (2013) stated:…”
Section: Methodological Limitationsmentioning
confidence: 99%
“…Common in the biological sciences, the idea of studying life state sequences (stages) was then being applied to a variety of family related research questions. For example, Martin (, ) reviewed the use and advantages of sequence analysis to the study of the family life course and how it may be used to test several hypotheses deduced from family development propositions.…”
Mattessich and Hill (1987) charted an historical overview of the family life cycle and development perspective in The Handbook of Marriage and the Family. That same year Evelyn Duvall presented a distinguished lecture at the National Council on Family Relations meeting titled, “Family Development's First Forty Years.” These academic works capture the historical foundation of family development theory by two pioneers of the theory and provide a reference point for discussing the history, current state, and future of the theory. In this article, Hill's and Duvall's historical accounts are summarized, contextualized, and used as a reference point to present four challenges to the future relevance of family development theory. Recommendations for future theory, research and practice are suggested.
“…Although Rodgers () predicted that stochastic modeling would be the future of development theory, referring specifically to the “game tree” analysis illustrated by Magrabi and Marshall (), White () had the advantage of almost 20 years of computational advancement when he demonstrated the potential of Rodgers's prediction. Similarly, Martin () benefited from another 20 years of advancement when he further demonstrated newer statistical techniques to test the complex propositions of development theory. In an overview of the general state of family theory, White () stated: It seems, however, the awareness of levels of analysis and the methodological and statistical advances we have experiences in the last few decades have “out paced” theoretical developments and our understanding of what is involved in constructing multilevel theories with cross‐level interaction.…”
Section: Methodological Limitationsmentioning
confidence: 99%
“…Although Rodgers (1973) predicted that stochastic modeling would be the future of development theory, referring specifically to the "game tree" analysis illustrated by Magrabi and Marshall (1965), White (1991) had the advantage of almost 20 years of computational advancement when he demonstrated the potential of Rodgers's prediction. Similarly, Martin (2015) benefited from another 20 years of advancement when he further demonstrated newer statistical techniques to test the complex propositions of development theory. In an overview of the general state of family theory, White (2013) stated:…”
Section: Methodological Limitationsmentioning
confidence: 99%
“…Common in the biological sciences, the idea of studying life state sequences (stages) was then being applied to a variety of family related research questions. For example, Martin (, ) reviewed the use and advantages of sequence analysis to the study of the family life course and how it may be used to test several hypotheses deduced from family development propositions.…”
Mattessich and Hill (1987) charted an historical overview of the family life cycle and development perspective in The Handbook of Marriage and the Family. That same year Evelyn Duvall presented a distinguished lecture at the National Council on Family Relations meeting titled, “Family Development's First Forty Years.” These academic works capture the historical foundation of family development theory by two pioneers of the theory and provide a reference point for discussing the history, current state, and future of the theory. In this article, Hill's and Duvall's historical accounts are summarized, contextualized, and used as a reference point to present four challenges to the future relevance of family development theory. Recommendations for future theory, research and practice are suggested.
“…1,37 Available Packages GMM can be implemented using Mplus software 1,2,15,37,41 and R through the lcmm package. 51,52 To our knowledge, GMM packages are not available in commercially-available statistical software such as SPSS, SAS, and others.…”
Section: Examples Of Studiesmentioning
confidence: 99%
“…113 However, it has been applied in many other contexts since then, including in epidemiology and public health, [114][115][116][117][118] as well as in psychology and social sciences. 4,51,[119][120][121][122] First, sequence analysis computes the matrix of dissimilarities or distances between individuals. These dissimilarity matrices are then used by classification approaches-mainly cluster analysis methods-to determine subgroups or classes of observations according to their similarity.…”
Trajectory modelling techniques have been developed to determine subgroups within a given population and are increasingly used to better understand intra- and inter-individual variability in health outcome patterns over time. The objectives of this narrative review are to explore various trajectory modelling approaches useful to epidemiological research and give an overview of their applications and differences. Guidance for reporting on the results of trajectory modelling is also covered. Trajectory modelling techniques reviewed include latent class modelling approaches, ie, growth mixture modelling (GMM), group-based trajectory modelling (GBTM), latent class analysis (LCA), and latent transition analysis (LTA). A parallel is drawn to other individual-centered statistical approaches such as cluster analysis (CA) and sequence analysis (SA). Depending on the research question and type of data, a number of approaches can be used for trajectory modelling of health outcomes measured in longitudinal studies. However, the various terms to designate latent class modelling approaches (GMM, GBTM, LTA, LCA) are used inconsistently and often interchangeably in the available scientific literature. Improved consistency in the terminology and reporting guidelines have the potential to increase researchers’ efficiency when it comes to choosing the most appropriate technique that best suits their research questions.
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