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Source: Psychological Methods
Resulting in 3 citations.
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Andersen, Henrik Kenneth |
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Equivalent Approaches to Dealing with Unobserved Heterogeneity in Cross-lagged Panel Models? Investigating the Benefits and Drawbacks of the Latent Curve Model with Structured Residuals and the Random Intercept Cross-lagged Panel Model Psychological Methods published online (16 December 2021): DOI: 10.1037/met0000285. Also: https://doi.org/10.1037/met0000285 Cohort(s): NLSY97 Publisher: American Psychological Association (APA) Keyword(s): Adolescent Behavior; Modeling; Smoking (see Cigarette Use); Statistical Analysis Panel models in structural equation modeling that combine static and dynamic components make it possible to investigate reciprocal relations while controlling for time-invariant unobserved heterogeneity. Recently, the latent curve model with structured residuals and the random-intercept cross-lagged panel model were suggested as "residual-level" versions of the more traditional autoregressive latent trajectory and dynamic panel models, respectively. Their main benefit is that they allow for a more straightforward interpretation of the trajectory factors. It is not widely known, however, that the residual-level models place potentially strong assumptions on the initial conditions--that is, the process that was occurring before the observation period began. If the process under investigation is not both stationary and at equilibrium then the residual-level models are not appropriate. They then do not control for all time-invariant unobserved heterogeneity and can result in biased cross-lagged and autoregressive estimates. I demonstrate this using the problem behavior of cigarette smoking among adolescents: Because the mean and variance of this process changes as a young person's smoking behavior develops, early stages of this process should not be examined using the residual-level models. This issue potentially exists for a wide variety of psychological and sociological subjects, essentially whenever the process under investigation is changing over the course of the observation period. This article discusses strategies to help researchers decide which model to use when, and compares some of their relative advantages and drawbacks. An amendment to the residual-level models is suggested in which the latent individual effects are allowed to covary with the initial residuals. This makes the residual-level models robust to violations of the assumptions surrounding the initial conditions, while retaining their other beneficial aspects. (PsycInfo Database Record (c) 2021 APA, all rights reserved) |
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Bibliography Citation
Andersen, Henrik Kenneth. "Equivalent Approaches to Dealing with Unobserved Heterogeneity in Cross-lagged Panel Models? Investigating the Benefits and Drawbacks of the Latent Curve Model with Structured Residuals and the Random Intercept Cross-lagged Panel Model." Psychological Methods published online (16 December 2021): DOI: 10.1037/met0000285.
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Biesanz, Jeremy C. Deeb-Sossa, Natalia Papadakis, Alison A. Bollen, Kenneth A. Curran, Patrick J. |
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The Role of Coding Time in Estimating and Interpreting Growth Curve Models Psychological Methods 9,1 (March 2004): 30-52. Also: http://psycnet.apa.org/journals/met/9/1/30/ Cohort(s): Children of the NLSY79 Publisher: American Psychological Association (APA) Keyword(s): Modeling, Growth Curve/Latent Trajectory Analysis; Weight The coding of time in growth curve models has important implications for the interpretation of the resulting model that are sometimes not transparent. The authors develop a general framework that includes predictors of growth curve components to illustrate how parameter estimates and their standard errors are exactly determined as a function of recoding time in growth curve models. Linear and quadratic growth model examples are provided, and the interpretation of estimates given a particular coding of time is illustrated. How and why the precision and statistical power of predictors of lower order growth curve components changes over time is illustrated and discussed. Recommendations include coding time to produce readily interpretable estimates and graphing lower order effects across time with appropriate confidence intervals to help illustrate and understand the growth process. |
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Bibliography Citation
Biesanz, Jeremy C., Natalia Deeb-Sossa, Alison A. Papadakis, Kenneth A. Bollen and Patrick J. Curran. "The Role of Coding Time in Estimating and Interpreting Growth Curve Models." Psychological Methods 9,1 (March 2004): 30-52.
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Ganzach, Yoav |
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Misleading Interaction and Curvilinear Terms Psychological Methods 2,3 (September 1997): 235-247. Also: http://psycnet.apa.org/journals/met/2/3/235/ Cohort(s): NLSY79 Publisher: American Psychological Association (APA) Keyword(s): Educational Aspirations/Expectations; Fathers, Influence; Modeling; Modeling, Nonparametric Regression; Mothers, Education; Parental Influences This article examines the relationships between interaction (product) terms and curvilinear (quadratic) terms in regression models in which the independent variables are correlated. The author uses 2 substantive examples to demonstrate the following outcomes: (a) If the appropriate quadratic terms are not added to the estimated model, then the observed interaction may indicate a synergistic (offsetting) relationship between the independent variables, whereas the true relationship is, in fact, offsetting (synergistic). (b) If the appropriate product terms are not added to the equation, then the estimated model may indicate concave (convex) relationships between the independent variables and the dependent variable, whereas the true relationship is, in fact, convex (concave). (c) If the appropriate product and quadratic terms are not examined simultaneously, then the observed interactive or curvilinear relationships may be nonsignificant when such relationships exist. The implications of these results for the examination of interaction and quadratic effects in multiple regression analysis are discussed. (PsycINFO Database Record (c) 2011 APA, all rights reserved) |
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Bibliography Citation
Ganzach, Yoav. "Misleading Interaction and Curvilinear Terms." Psychological Methods 2,3 (September 1997): 235-247.
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