lcsm: An R package and tutorial on latent change score modelling

Latent change score models (LCSMs) are used across disciplines in behavioural sciences to study how constructs change over time. LCSMs can be used to estimate the trajectory of one construct (univariate) and allow the investigation of how changes between two constructs (bivariate) are associated with each other over time. This paper introduces the R package lcsm, a tool that aims to help users understand, analyse, and visualise different latent change score models. The lcsm package provides functions to generate model syntax for basic univariate and bivariate latent change score models with different model specifications. It is also possible to visualise different model specifications in simplified path diagrams. An interactive application illustrates the main functions of the package and demonstrates how the model syntax and path diagrams change based on different model specifications. This R package aims to increase the transparency of reporting analyses and to provide an additional resource to learn latent change score modelling.

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A62 A major likelihood-based approach gives problematic estimates of diversification dynamics and rates

Virus Evolution ◽

10.1093/ve/vez002.061 ◽

2019 ◽

Vol 5 (Supplement_1) ◽

Author(s):

Chenlu Di ◽

Andreas L S Meyer ◽

John J Wiens

Keyword(s):

R Package ◽

Change Over Time ◽

Diversity Patterns ◽

Significant Relationships ◽

Correct Model ◽

Speciation Rates ◽

Incorrect Model ◽

Diversity Of Life ◽

Over Time

Abstract The diversity of life is shaped by rates of speciation and extinction, and so estimating these rates correctly is crucial for understanding diversity patterns among clades, regions, and habitats. In 2011, Morlon and collaborators developed a promising likelihood-based approach to estimate speciation and extinction and to infer the model describing how these rates change over time based on AICc. This approach is now implemented in an R package (RPANDA). Here, we test the accuracy of this approach under simulated conditions, to evaluate its ability to correctly estimate rates of speciation, extinction, and diversification (speciation—extinction) and to choose the correct underlying model of diversification (e.g. constant or changing rates of speciation and extinction over time). We found that this likelihood-based approach frequently picked the incorrect model. For example, with changing speciation rates over time, the correct model was chosen in only ∼10 per cent of replicates. There were significant relationships between true and estimated speciation rates using this approach, but relationships were weak when speciation rates were constant within clades. Relationships were consistently weak between true and estimated rates of extinction and of diversification. Overall, we suggest that results from this approach should be interpreted with considerable caution.

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Motivation-achievement cycle in learning: an intensive longitudinal latent change study

10.31234/osf.io/fgchj ◽

2019 ◽

Author(s):

Tuong-Van Vu ◽

Martijn Meeter ◽

Abe Dirk Hofman ◽

Brenda Jansen ◽

Lucía Magis-Weinberg ◽

...

Keyword(s):

Simulated Data ◽

Change Score ◽

Multiple Time ◽

Main Question ◽

Modeling Framework ◽

Data Set ◽

Latent Change Score ◽

Multiple Time Points ◽

Over Time ◽

Motivation And Achievement

The present research investigates the relations between motivation belief, motivational behaviors and academic achievement in educational contexts. The first main question is whether motivational belief is reciprocally related to achievement and whether a cyclic loop of motivation and achievement is formed over time. The second objective is to study the mediating pathway between motivation and achievement by measuring actual effort spent on learning (i.e. motivational behaviors). Third, we examine the causality of these relations by investigating how they are affected when achievement is experimentally manipulated. We design an intensive longitudinal experiment in which participants will learn new English vocabulary and their motivational belief, effort, and achievement are measured at multiple time points. In the second half of the experiment, participants receive rigged feedback that their achievement has dropped which is expected to influence their subsequent motivation, effort, and actual achievement. To study these dynamics, the changes in one construct are related to changes in other constructs over time, and will be analyzed within a latent change score modeling framework. Planned analyses, expected (narrative) results, and a simulated data set are provided.

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Social Isolation and Memory Decline in Later-life

The Journals of Gerontology Series B ◽

10.1093/geronb/gbz152 ◽

2019 ◽

Vol 75 (2) ◽

pp. 367-376 ◽

Cited By ~ 8

Author(s):

Sanna Read ◽

Adelina Comas-Herrera ◽

Emily Grundy

Keyword(s):

Social Isolation ◽

Later Life ◽

Change Score ◽

Memory Decline ◽

Latent Change Score ◽

High Level ◽

Older Men And Women ◽

English Longitudinal Study ◽

Poor Memory ◽

Over Time

Abstract Objectives To investigate associations between level and changes in social isolation and in memory in older men and women. Methods The sample included 6,123 women and 5,110 men aged 50+ from the English Longitudinal Study of Aging (ELSA). Extended latent change score models from six measurement occasions every 2 years from 2002 were used to investigate associations between social isolation and memory. Models were adjusted for age, socioeconomic position, and health. Results Social isolation increased and memory decreased over time. Among men an initially high level of social isolation was associated with a somewhat greater decrease in memory. Among women a greater increase in social isolation predicted a greater decrease in memory and a larger change in social isolation was associated with further larger changes in isolation, although when social isolation reached a higher level it subsequently decreased. Conclusions Results suggest that the association between social isolation and memory decline arises because social isolation is associated with increased memory decline rather than poor memory leading to increases in social isolation. Men with high levels of social isolation and women with accumulated social isolation over time are especially affected as these patterns of isolation were associated with more profound memory decline.

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Modeling Retest Effects in Developmental Processes Using Latent Change Score Models

10.31234/osf.io/gu78q ◽

2021 ◽

Author(s):

Rohit Batra ◽

Silvia A. Bunge ◽

Emilio Ferrer

Keyword(s):

Repeated Measures ◽

Change Score ◽

Sequential Design ◽

Developmental Processes ◽

Fluid Reasoning ◽

Development Processes ◽

Alternative Approaches ◽

Latent Change Score ◽

Changes Over Time ◽

Over Time

Studying development processes, as they unfold over time, involves collecting repeated measures from individuals and modeling the changes over time. One methodological challenge in this type of longitudinal data is separating retest effects, due to the repeated assessments, from developmental processes such as maturation or age. In this article, we describe several specifications of latent change score models using age as the underlying time metric and include parameters to account for retest effects. We illustrate the models with data on fluid reasoning collected from children and adolescents in a cohort-sequential design ranging from 6 to 20 years. Our models include alternative approaches to specify retest effects at the structural or measurement level of the model, and as an observed or a latent covariate. We discuss the benefits and limitations of the different approaches for univariate and multivariate data in the context of studying developmental processes.

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