Growth Curve Modeling

Panik, Michael J.

doi:10.1002/9781118763971

Cited by 66 publications

(33 citation statements)

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“…The modelling framework followed that described by Stirrup et al [17], but with an extension to the asymptotic growth curve attributed to Janoshek and Sager [19] to model the shape of post-treatment recovery in CD4 counts:…”

Section: Discussionmentioning

confidence: 99%

Predictors of CD4 cell recovery following initiation of antiretroviral therapy among HIV‐1 positive patients with well‐estimated dates of seroconversion

Stirrup

Copas

et al. 2017

HIV Medicine

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ObjectivesTo investigate factors that predict speed of recovery and long‐term CD4 cell count in HIV‐1 seroconverters initiating combination antiretroviral therapy (cART), and to quantify the influence of very early treatment initiation. We make use of all pre‐treatment CD4 counts, because analyses using only a single observation at initiation may be subject to biases.MethodsWe used data from the CASCADE (Concerted Action on SeroConversion to AIDS and Death in Europe) multinational cohort collaboration of HIV‐1 seroconverters. We analysed pre‐ and post‐treatment data of patients with seroconversion dates estimated January 2003–March 2014 (n = 7600 for primary analysis) using a statistical model in which the characteristics of recovery in CD4 counts are determined by multiple predictive factors. Secondary analyses were performed incorporating uncertainty in the exact timing of seroconversion to allow more precise estimation of the benefit of very early treatment initiation.Results‘True’ CD4 count at cART initiation was the strongest predictor of CD4 count beyond 3 years on cART. Allowing for lack of complete certainty in the date of seroconversion, CD4 recovery was more rapid for patients in whom treatment was initiated within 4 months. For a given CD4 count, higher viral load (VL) at initiation was strongly associated with higher post‐treatment CD4 recovery. For other patient and drug characteristics, associations with recovery were statistically significant but small in magnitude.Conclusions CD4 count at cART initiation is the most important factor in predicting post‐treatment recovery, but VL provides substantial additional information. If cART is initiated in the first 4 months following seroconversion, recovery of CD4 counts appears to be more rapid.

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Section: Discussionmentioning

confidence: 99%

Predictors of CD4 cell recovery following initiation of antiretroviral therapy among HIV‐1 positive patients with well‐estimated dates of seroconversion

Stirrup

Copas

et al. 2017

HIV Medicine

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“…The choice of functional forms for the relationships between the local parameters and the growth intensity factor can affect the accuracy of the models. The steps in building a GADA model are [ 16 ]: Select a base equation. e.g.…”

Section: Introductionmentioning

confidence: 99%

“…The g-GADA method has not received much attention in the literature and consequently has been re-discovered over the years [ 16 , 19 , 20 , 21 ]. It is most useful when two or more parameters are local.…”

Section: Introductionmentioning

confidence: 99%

Engelmann Spruce Site Index Models: A Comparison of Model Functions and Parameterizations

Nigh

2015

PLoS ONE

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Engelmann spruce (Picea engelmannii Parry ex Engelm.) is a high-elevation species found in western Canada and western USA. As this species becomes increasingly targeted for harvesting, better height growth information is required for good management of this species. This project was initiated to fill this need. The objective of the project was threefold: develop a site index model for Engelmann spruce; compare the fits and modelling and application issues between three model formulations and four parameterizations; and more closely examine the grounded-Generalized Algebraic Difference Approach (g-GADA) model parameterization. The model fitting data consisted of 84 stem analyzed Engelmann spruce site trees sampled across the Engelmann Spruce – Subalpine Fir biogeoclimatic zone. The fitted models were based on the Chapman-Richards function, a modified Hossfeld IV function, and the Schumacher function. The model parameterizations that were tested are indicator variables, mixed-effects, GADA, and g-GADA. Model evaluation was based on the finite-sample corrected version of Akaike’s Information Criteria and the estimated variance. Model parameterization had more of an influence on the fit than did model formulation, with the indicator variable method providing the best fit, followed by the mixed-effects modelling (9% increase in the variance for the Chapman-Richards and Schumacher formulations over the indicator variable parameterization), g-GADA (optimal approach) (335% increase in the variance), and the GADA/g-GADA (with the GADA parameterization) (346% increase in the variance). Factors related to the application of the model must be considered when selecting the model for use as the best fitting methods have the most barriers in their application in terms of data and software requirements.

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“…Some students participated in the study once, twice or three times. In order to evaluate this longitudinal data set, statistical models that measure change are needed (for literature on growth curve modeling, see Grimm, Ram, & Estabrook (2017) and Panik (2014)). In view of the unbalanced data set of this study (Luke, 2004, p. 63), multilevel models for a longitudinal data set are especially suitable (Hox 2011;Raudenbush & Bryk 2002).…”

Section: Methodsmentioning

confidence: 99%

Knowledge Growth, Academic Beliefs and Motivation of Students in Business and Economics - A longitudinal German Case Study

Biewen¹,

Happ²,

Schmidt³

et al. 2018

HES

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In this study we examine the determinants of and the relationship among economic knowledge, epistemological beliefs, and extrinsic and intrinsic motivation over the course of undergraduate studies in a sample of students of business and economics at a university in Germany. We found economic knowledge increased over the course of studies, extrinsic and intrinsic motivation declined, and students became more skeptical in their epistemological beliefs about the objectivity of economic content being taught in their courses. The students" level of economic knowledge was related to intrinsic motivation but unrelated to extrinsic motivation and epistemological beliefs. Furthermore, the students" tendency to become more skeptical over the course of their studies was mitigated by high levels of extrinsic motivation.

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Growth Curve Modeling

Cited by 66 publications

References 0 publications

Predictors of CD4 cell recovery following initiation of antiretroviral therapy among HIV‐1 positive patients with well‐estimated dates of seroconversion

Predictors of CD4 cell recovery following initiation of antiretroviral therapy among HIV‐1 positive patients with well‐estimated dates of seroconversion

Engelmann Spruce Site Index Models: A Comparison of Model Functions and Parameterizations

Knowledge Growth, Academic Beliefs and Motivation of Students in Business and Economics - A longitudinal German Case Study

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