Comparing methods of classifying life courses: sequence analysis and latent class analysis

Han, Yu; Liefbroer, Aart C.; Elzinga, Cees H.

doi:10.14301/llcs.v8i4.409

Cited by 36 publications

(36 citation statements)

References 49 publications

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“…It is opposed to conventional approaches in epidemiology that consider each state independently from one another. The comparison of SSA with other methods, which can be appropriate for the study of a care pathway, such as latent class analysis (LCA), revealed that both methodologies yield similar clustering results 41,49,50 . These studies have highlighted that SSA is easier to use and to compute than LCA and that, unlike LCA, it does not require specification of a model.…”

Section: Table 4 Here 4 Discussionmentioning

confidence: 99%

“…We propose to use a combination of the two main criteria 38 : the weighted average silhouette width (ASWw) 38,39 and the Hubert's C index 40 allow for the optimal number of clusters to be set. The choice of these two parameters is in line with a recent social sciences paper, in which three criteria were selected for the partition 41 , namely the ASWw, Hubert's C index, and the point biserial correlation (PBC). We chose to forego the PBC as it usually led to the same choice of the number of clusters as the two other criteria.…”

Section: The 3 Rd Step Of Ssa: Clustering Sequencesmentioning

confidence: 99%

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Use of state sequence analysis for care pathway analysis: The example of multiple sclerosis

Roux

Grimaud

Leray

2018

Stat Methods Med Res

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The concept of care pathways is increasingly being used to enhance the quality of care and to optimize the use of resources for health care. We here propose an innovative method in epidemiology that is derived from social sciences: state sequence analysis (SSA). This method takes into account the chronology of care consumption and allows for identification of specific patterns. A process for using SSA in the health area is proposed and discussed. The main steps are: data coding, measurement of dissimilarities between sequences (focusing on optimal matching methods and the choice of related costs), and application of a clustering method to obtain a typology of sequence patterns. As an example of its use in the health area, SSA was employed to analyse care pathways of a random sample of patients with multiple sclerosis. This sample has been selected from the main French healthcare database covering the period 2007 to 2013 ( n = 1 000). A five-cluster typology was obtained which allowed distinction of care consumption groups. Overall, about half of the patients had low care consumption, about one quarter had medium to high consumption, and another quarter had high consumption. We conclude that state sequence analysis is an innovative and flexible methodology that is worth considering in health care research.

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Section: Table 4 Here 4 Discussionmentioning

confidence: 99%

Section: The 3 Rd Step Of Ssa: Clustering Sequencesmentioning

confidence: 99%

Use of state sequence analysis for care pathway analysis: The example of multiple sclerosis

Roux

Grimaud

Leray

2018

Stat Methods Med Res

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“…Next, we perform a hierarchical cluster analysis on this distance matrix using Ward's method, which implies that sequences with the smallest distance from each other are clustered. To determine the most appropriate number of clusters, we consider two cluster cutoff criteria-namely, the average silhouette widths (ASW) and point biserial correlation (PBC) (Studer 2013)-as well as the construct validity of the cluster solution, by comparing the fit of regressions of the different cluster-solutions on earnings-Akaike information criterion (AIC) and Bayesian information criterion (BIC) (Han et al 2017;Warren et al 2015). We use the TraMineR package in R to perform the sequence cluster analysis (Gabadinho et al 2011).…”

Section: Analytical Approachmentioning

confidence: 99%

The Long-Term Costs of Family Trajectories: Women’s Later-Life Employment and Earnings Across Europe

2020

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The "motherhood earnings penalty" is a well-established finding in many Western countries. However, a divide between mothers and nonmothers might oversimplify reality given that the family life course has diversified over the last decades. In addition, whether family choices have consequences for women's employment and earnings in later life is not well known, particularly in a comparative perspective. Using data on 50-to 59-year-old women from the Generations and Gender Programme, the British Household Panel Survey, and SHARELIFE for 22 European countries, we derive a typology of women's family trajectories and estimate its association with women's later-life employment and earnings. Whereas family trajectory-related differences with regard to employment were relatively small, our findings reveal a clear, long-lasting family trajectory gradient in earnings. Childless women (with or without a partner) as well as single mothers had higher personal earnings than women whose family trajectories combined parenthood and partnership. Moreover, in societies in which reconciliation of work and family during midlife is less burdensome, labor market outcomes of women following different family trajectories converge. Our findings show that women's fertility and partnership behavior are inevitably interrelated and jointly influence employment and earning patterns until later in life. The results imply that promoting equal employment opportunities could have long-lasting effects on women's economic independence.

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“…Scientists can choose to prioritize indels to focus on duration in a state or substitution to focus on timing and order. Subsequence‐based metrics, as opposed to OM's edit‐based metrics, can also be used in sequence analyses, but OM has routinely outperformed when the life course sequences are related to family formation (Aisenbrey & Fasang, ; Han, Liefbroer, & Elzinga, ).…”

Section: Conceptualizing and Operationalizing Family Structure Historiesmentioning

confidence: 99%

Two Methods for Studying the Developmental Significance of Family Structure Trajectories

Johnston

Crosnoe

Mernitz

et al. 2019

J of Marriage and Family

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Objective: The objective of this research note is to use both sequence analysis (SA) and repeated-measures latent class analysis (LCA) to identify children's family structure trajectories from birth through age 15 and compare how the two sets of trajectories predict alcohol use across the transition from adolescence into young adulthood. Background: Contemporary family scholars have studied the influence of changes in family structure, often referred to as family structure instability, on child and adolescent development. Typically, this research has focused on either the number or type of transitions children have experienced, but statistical advances are increasing the viability of more complex person-centered approaches to this issue, such as SA and LCA. The choice to use one approach or the other, however, is often discipline specific and relies on different assumptions and

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Comparing methods of classifying life courses: sequence analysis and latent class analysis

Abstract: We compare life course typology solutions generated by sequence analysis (SA)

Cited by 36 publications

References 49 publications

Use of state sequence analysis for care pathway analysis: The example of multiple sclerosis

Use of state sequence analysis for care pathway analysis: The example of multiple sclerosis

The Long-Term Costs of Family Trajectories: Women’s Later-Life Employment and Earnings Across Europe

Two Methods for Studying the Developmental Significance of Family Structure Trajectories

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