Sequence Analysis: Where Are We, Where Are We Going?

Ritschard, Gilbert; Studer, Matthias

doi:10.1007/978-3-319-95420-2_1

Cited by 33 publications

(40 citation statements)

References 41 publications

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“…To reconstruct the trajectory types in the two domains of interest, we used multichannel sequence analysis (MCSA) [ 39 ], an extension of traditional sequence analysis [ 40 ]. MCSA is a longitudinal statistical technique useful for exploratory studies in which the main aim is to understand unknown long-term patterns in different life domains through highly illustrative visualizations and a holistic perspective, focusing on the whole trajectory rather than on specific transitions that compose a trajectory [ 40 ]. MCSA simultaneously estimates typical life trajectories in more than one domain, relying on the analysis of similarities between all possible pairs of individual trajectories in those domains.…”

Section: Methodsmentioning

confidence: 99%

Association between Lifetime Tobacco Use and Alcohol Consumption Trajectories and Cardiovascular and Chronic Respiratory Diseases among Older People

Madero-Cabib

Bambs

2021

IJERPH

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Background: We identify representative types of simultaneous tobacco use and alcohol consumption trajectories across the life course and estimate their association with cardiovascular and chronic respiratory diseases (CVDs and CRDs) among older people in Chile. Methods: We used data from a population-representative, face-to-face and longitudinal-retrospective survey focused on people aged 65–75 (N = 802). To reconstruct trajectory types, we employed weighted multichannel sequence analysis. Then, we estimated their associations with CVDs and CRDs through weighted logistic regression models. Results: Long-term exposure to tobacco use and alcohol consumption across life are associated with the highest CVD and CRD risks. Long-term nonsmokers and nondrinkers do not necessarily show the lowest CVDs and CRDs risks if these patterns are accompanied by health risk factors such as obesity or social disadvantages such as lower educational levels. Additionally, trajectories showing regular consumption in one domain but only in specific periods of life, whether early or late, while maintaining little or no consumption across life in the other domain, lead to lower CVDs or CRDs risks than trajectories indicating permanent consumption in both domains. Conclusions: A policy approach that considers CVDs and CRDs as conditions that strongly depend on previous individual experiences in diverse life domains can contribute to the improved design and evaluation of preventive strategies of tobacco use and alcohol consumption across the life course.

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Section: Methodsmentioning

confidence: 99%

Association between Lifetime Tobacco Use and Alcohol Consumption Trajectories and Cardiovascular and Chronic Respiratory Diseases among Older People

Madero-Cabib

Bambs

2021

IJERPH

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“…Regarding management of missing data in sequence analysis, Gabadinho et al (2011) 125 and Halpin (2016) 130 have suggested many approaches such as multiple imputation for categorical data and taking into account the position of the missing value on the time axis (left, inbetween and right missing values). However, as Ritschard and Studer (2018) 123 highlighted, this issue have no definitive solution and deserve further research.…”

Section: Advantages and Limitationsmentioning

confidence: 99%

“…These dissimilarity matrices are then used by classification approaches-mainly cluster analysis methods-to determine subgroups or classes of observations according to their similarity. 18,123 Based on a previous "multidimensional model of care trajectories", 112 a comprehensive approach of sequence analysis, considering simultaneously illness condition, care providers and care settings, has recently been proposed. 124 As in other classification methods presented in this review, subgroup membership can be used as a dependent or independent variable to explore predictors of health trajectories and their contribution to future outcomes.…”

Section: Presentationmentioning

confidence: 99%

See 1 more Smart Citation

<p>Trajectory Modelling Techniques Useful to Epidemiological Research: A Comparative Narrative Review of Approaches</p>

Nguefack

Pagé

Katz

et al. 2020

CLEP

187

145

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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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“…SPM accounts for the chronological, time ordered relationships between events [30]. Therefore, the method has been embraced widely by social scientists in modeling life course studies, e.g., the trajectories of careers, marital status or health trajectories [31]. Our study takes advantage of the developments of LA, life course studies, and data-mining methods to model the longitudinal trajectories of engagement 3 Methods…”

Section: Learning Analytics and Modeling The Engagementmentioning

confidence: 99%

The trajectory of early disengagement: A longitudinal learning analytics study over a full program

Saqr

López-Pernas

2021

Preprint

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Research on online engagement is abundant. However, most of the available studies have focused on a single course. Therefore, little is known about how students’ online engagement evolves over time. Previous research in face-to-face settings has shown that early disengagement has negative consequences on students’ academic achievement and graduation rates. This study examines the longitudinal trajectory of students’ online engagement throughout a complete college degree. The study followed 99 students over 4 years of college education including all their course data (15 courses and 1383 course enrollments). Students’ engagement states for each course enrollment were identified through Latent Class Analysis (LCA). Students who were not engaged at least one course in the first term were labeled as “Early Disengagement”, whereas the remaining students were labeled as “Early Engagement”. The two groups of students were analyzed using sequence pattern mining methods. The stability (persistence of the engagement state), transition (ascending to a higher engagement state or descending to a lower state), and typology of each group trajectory of engagement are described in this study. Our results show that early disengagement is associated with higher rates of dropout, lower scores and lower graduation rates whereas early engagement is relatively stable. Our findings indicate that it is critical to proactively address early disengagement during a program, watch the alarming signs such as presence of disengagement during the first courses, declining engagement along the program or history of frequent disengagement states.

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Sequence Analysis: Where Are We, Where Are We Going?

Cited by 33 publications

References 41 publications

Association between Lifetime Tobacco Use and Alcohol Consumption Trajectories and Cardiovascular and Chronic Respiratory Diseases among Older People

Association between Lifetime Tobacco Use and Alcohol Consumption Trajectories and Cardiovascular and Chronic Respiratory Diseases among Older People

<p>Trajectory Modelling Techniques Useful to Epidemiological Research: A Comparative Narrative Review of Approaches</p>

The trajectory of early disengagement: A longitudinal learning analytics study over a full program

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