REACH Dictionary
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"Using a map and compass to travel from one place to another.”
Blaisure, K. R., Saathoff-Wells, T., Pereira, A., MacDermid Wadsworth, S., & Dombro, A. L. (2015). Serving military families -theories, research, and application. Taylor & Francis Ltd.
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Military
“A university established in each state on land granted to the state by the federal government to make education more accessible to the working class and to teach agriculture, engineering, sciences, and military tactics; to conduct research; and to provide extension services.”
Blaisure, K. R., Saathoff-Wells, T., Pereira, A., MacDermid Wadsworth, S., & Dombro, A. L. (2015). Serving military families -theories, research, and application. Taylor & Francis Ltd.
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Programs/Resources
Latent class analysis "identifies unobservable (latent) subgroups within a population based on individuals' responses to multiple observed variables."
Latent transition analysis. (n.d.). Retrieved April 18, 2019, from https://www.methodology.psu.edu/ra/lta/
Latent class growth analysis is used to identify distinct classes, or subgroups, in a population. This analysis assumes the growth trajectories within each class are homogenous, as they are assumed to be fixed at zero.
Jung, T., & Wickrama, K. A. S. (2008). An introduction to latent class growth analysis and growth mixture modeling. Social and Personality Psychology Compass, 2(1), 302–317. https://doi.org/10.1111/j.1751-9004.2007.00054.x
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Methodology
The latent congruency model is a measurement model designed for organizational research which creates two factors to represent the mean and difference of two interdependent component measures. It can estimate and control for measurement error, provide straightforward ways for examining measurement equivalence, allow for the examination of complex theoretical models, and allow the examination antecedents and consequences of congruence constructs and component measures.
Cheung, G. W. (2009). Introducing the latent congruence model for improving the assessment of similarity, agreement, and fit in organizational research. Organizational Research Methods, 12(1), 6-33. https://doi.org/10.1177/1094428107308914.
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Methodology
Latent constructs are abstract variables which cannot be observed or measured directly.
Maruyama, G. and Ryan, C. S. (2014) Research Methods in Social Relations. West Sussex: John Wiley and Sons Ltd. Allen, K. R., & Henderson, A. C. (2017). Family theories: Foundations and applications. West Sussex, UK: John Wiley & Sons Ltd.
"Latent growth models (LGMs) are a special class of confirmatory factor analysis models used specifically to model trajectories over time. These trajectories in most cases are linear, but can encompass other trajectories such as a quadratic slope or even slopes that are freely varying."
Lin, J. (2021, August 16). Latent growth models and measurement invariance with R in lavaan [video file]. Retreived from https://stats.oarc.ucla.edu/r/seminars/lgm/#s1
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Methodology
Latent profile analysis can model relationships between three or more variables by identifying groups in a sample with similar patterns of variables.
Stanley, L., Kellermanns, F. W., & Zellweger, T. M. (2017). Latent profile analysis: Understanding family firm profiles. Family Business Review, 30(1), 84-102. https://doi.org/10.1177/0894486516677426
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Methodology
Latent transition analysis "is an extension of LCA that uses longitudinal data to identify movement between the subgroups over time."
Latent transition analysis. (n.d.). Retrieved April 18, 2019, from https://www.methodology.psu.edu/ra/lta/
An analytical technique within the structural equation modeling framework to examine longitudinal change over time. It considers change over time in terms of an underlying, latent, or unobserved variable. It can represent unique curves for individuals or groups. It is also flexible in that a latent growth curve analysis can analyze and model a range of parameters all at once, starting with a single growth trajectory with a single variable to more complex models with several variables.
Murphy, K., Sloper, M., Berry, T. (2014). Innovative Statistical Solutions for Evaluation Data: Latent Growth Curve Modeling to Examine Change Over Time. American Evaluation Association. https://comm.eval.org/HigherLogic/System/DownloadDocumentFile.ashx?DocumentFileKey=9402a686-aaba-48ae-b41c-361937b8cbf1
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Methodology