Mixed-effects Modeling Approach Research Articles

Integrating regional climate change into allometric equations for estimating tree aboveground biomass of Masson pine in China

A climate-sensitive aboveground biomass (AGB) equation, in combination with nonlinear mixed-effects modeling and dummy variable approach, was developed to examine how climate change may affect the allometric relationships between tree diameter and biomass. We showed that such changes in allometry need to be taken into account for estimating tree AGB in Masson pine. As a native species and being widely distributed in subtropical China, Masson pine (Pinus massoniana Lamb.) forests play a pivotal role in maintaining forest ecosystem functions and mitigation of carbon concentration increase at the atmosphere. Traditional biomass allometric equations do not account for a potential effect of climate on the diameter–biomass relationships. The amplitude of such an effect remains poorly documented. We presented a novel method for detecting the long-term (2041–2080) effects of climate change on the diameter–biomass relationships and the potential consequences for long-term changes of biomass accumulation for Masson pine. Our approach was based on a climate-sensitive AGB model developed using a combined nonlinear mixed-effects model and dummy variable approach. Various climate-related variables were evaluated for their contributions to model improvement. Heteroscedasticity was accounted for by three residual variance functions: exponential function, power function, and constant plus function. The results showed that diameter at breast height, together with the long-term average of growing season temperature, total growing season precipitation, mean temperature of wettest quarter, and precipitation of wettest quarter, had significant effects on values of AGB. Excessive rain during the growing season and high mean temperature in the wettest quarter reduced the AGB, while a warm growing season and abundant precipitation in the wettest quarter increased the AGB. Climate change significantly affected the allometric scale of biomass equation. The new climate-sensitive allometric model developed in this study may improve biomass predictions compared with the traditional model without climate effects. Our findings suggested that the AGB of Masson pine trees with the same diameter at breast height under three climate scenarios including representative concentration pathway (RCP) 2.6, RCP 4.5, and RCP 8.5 in the future period 2041–2080 would increase by 24.8 ± 32.7% (mean ± standard deviation), 27.0 ± 33.4%, and 27.7 ± 33.8% compared with the constant climate (1950–2000), respectively. As a consequence, we may expect a significant regional variability and uncertainty in biomass estimates under climate change.

First plasma and tissue pharmacokinetic study of the YSNSG cyclopeptide, a new integrin antagonist, using microdialysis

The YSNSG peptide is a synthetic peptide targeting αvβ3 integrin. This peptide exhibits promising activity in vitro and in vivo against melanoma. To determine pharmacokinetic parameters and predictive active doses in the central nervous system (CNS) and subcutaneous tissue (SC), we conducted microdialysis coupled with pharmacokinetic modeling and Monte Carlo simulation. After a recovery period of surgical procedures, a microdialysis probe was inserted in the caudate and in subcutaneous tissue. Plasma samples and dialysates collected 5h after YSNSG intravenous administration (10mg/kg) were analyzed by UPLC-MS/MS. A nonlinear mixed-effect modeling approach implemented in Monolix® 2016R1 was performed. Model selection and evaluation were based on the usual diagnostic plot, precision and information criteria. The primary plasma and tissue pharmacokinetic parameters were comparable with those of other integrin antagonists, such as cilengitide or ATN-161. Tissue/plasma and brain/plasma area under the curve (AUC) ratio were 66.2±21.6% and 3.6±4.7%, respectively. Two models of 2-compartments with an additional microdialysis compartment, parameterized as rate constants (k for elimination, k12/k21 and k13/k31 for distribution) and volumes (central V1 and peripheral microdialysis compartment V3) with zero-order input were selected to describe the dialysate concentrations in CNS and SC. The inter-individual variability (IIV) was described by exponential terms, and residual variability was described by a combined additive and proportional error model. Individual AUC (plasma and tissues) values were derived for each animal using the Empirical-Bayes-Estimates of the individual parameters. The regimens needed to achieve an in vitro predetermined target concentration in tissues were studied by Monte Carlo simulations using Monolix® 2016R1. YSNSG pharmacokinetic parameters show promising results in terms of subcutaneous disposition. Further investigations into such processes as encapsulation and intratumoral disposition are currently being conducted.

Predictive models of poly(ethylene-terephthalate) film degradation under multi-factor accelerated weathering exposures.

Accelerated weathering exposures were performed on poly(ethylene-terephthalate) (PET) films. Longitudinal multi-level predictive models as a function of PET grades and exposure types were developed for the change in yellowness index (YI) and haze (%). Exposures with similar change in YI were modeled using a linear fixed-effects modeling approach. Due to the complex nature of haze formation, measurement uncertainty, and the differences in the samples’ responses, the change in haze (%) depended on individual samples’ responses and a linear mixed-effects modeling approach was used. When compared to fixed-effects models, the addition of random effects in the haze formation models significantly increased the variance explained. For both modeling approaches, diagnostic plots confirmed independence and homogeneity with normally distributed residual errors. Predictive R2 values for true prediction error and predictive power of the models demonstrated that the models were not subject to over-fitting. These models enable prediction under pre-defined exposure conditions for a given exposure time (or photo-dosage in case of UV light exposure). PET degradation under cyclic exposures combining UV light and condensing humidity is caused by photolytic and hydrolytic mechanisms causing yellowing and haze formation. Quantitative knowledge of these degradation pathways enable cross-correlation of these lab-based exposures with real-world conditions for service life prediction.

Tree diameter increments following silvicultural treatments in a dipterocarp forest in Kalimantan, Indonesia: A mixed-effects modelling approach

An individual-tree-based growth-and-yield model (SILFOR) was developed to evaluate the long-term effects of silvicultural treatments beyond logging in a tropical forest is described. Here we focus on the model’s approach to prediction of the magnitude and duration of silvicultural treatment effects on growth of the residual trees that will contribute most of the timber available to the next planned harvest in 25–40years. Data from 30 1-ha permanent sample plots monitored for up to 20years in dipterocarp forest in Kalimantan, Indonesia were used to develop the model. The treatments were different logging intensities with or without post-logging silvicultural treatments. Each species was assigned to one of five groups based on their ecological traits and the merchantability of their timber. A mixed-effects model was used to account for the spatially and temporally autocorrelated permanent plot data.The mixed-effects approach improved model performance substantially compared to a fixed-effects approach; specification of the variance function and correlation structure of the error term further improved model fit. Patterns and rates of tree diameter increment varied substantially, as indicated by the large differences among species groups in terms of the level of random-effects, number of parameters assigned as mixed-effects, and the covariates that define the best model. Similarly, silvicultural treatment effects also varied among species groups, as indicated by differences in the treatment dummy variables in the final model. Among-treatment differences diminished over time. We also found that species group representation is effected differentially by the silvicultural treatments. Overall, the study presents a novel and hopefully useful approach to the analysis of growth-and-yield data from tropical forests under intensified management for timber.

Effects of early respacing on the density and microfibril angle of Sitka spruce wood

Although significant advances have been made in modelling the effects of silviculture on wood properties, few models have been calibrated using data from long-term stand density or respacing experiments. In this study we examined the effects of early respacing on the density and microfibril angle (MfA) of Sitka spruce (Picea sitchensis [Bong.] Carr.) wood using samples taken from a fully-replicated 57-year-old trial located in Northern Ireland, which had been thinned at age 11 years. Using a mixed-effects modelling approach, radial profiles of density and MfA from four different respacing treatments (1.83 m × 3.66 m, 3.66 m × 3.66 m, 3.66 m × 5.49 m and 5.49 m × 5.49 m) were compared with those of timber from an unthinned control (1.83 m × 1.83 m). After accounting for radial position and ring width, we found significant differences in both density and MfA between respacing treatments. Mean predicted values of wood density for rings 40–50 were 400 and 494 kg m⁻³ for the widest respacing treatment and the unthinned control, respectively, and fell between these two extremes for the other respacing treatments. Predicted latewood proportions in ring 50 were 12 and 22 per cent, for the same respacing treatments, respectively. There was some evidence of an age-related decline in wood density in the two narrowest respacing treatments. While there was a significant effect of respacing on MfA variation, the trends between respacing treatments were less apparent. Overall, these results indicate that the timing of respacing treatments is an important consideration in Sitka spruce management; early and severe respacing should be avoided to avoid deleterious effects on wood density and MfA.

Efficacy of Internet-Based Cognitive Behavioral Therapy in Improving Sexual Functioning of Breast Cancer Survivors: Results of a Randomized Controlled Trial.

Purpose We evaluated the effect of Internet-based cognitive behavioral therapy (CBT) on sexual functioning and relationship intimacy (primary outcomes) and body image, menopausal symptoms, marital functioning, psychological distress, and health-related quality of life (secondary outcomes) in breast cancer survivors (BCSs) with a DSM-IV diagnosis of a sexual dysfunction. Patients and Methods We randomly assigned 169 BCSs to either Internet-based CBT or a waiting-list control group. The CBT consisted of weekly therapist-guided sessions, with a maximum duration of 24 weeks. Self-report questionnaires were completed by the intervention group at baseline (T0), midtherapy (T1), and post-therapy (T2) and at equivalent times by the control group. We used a mixed-effect modeling approach to compare the groups over time. Results Compared with the control group, the intervention group showed a significant improvement over time in overall sexual functioning (effect size for T2 [EST2] = .43; P = .031), which was reflected in an increase in sexual desire (EST1 = .48 and EST2 = .72; P < .001), sexual arousal (EST2 = .50; P = .008), and vaginal lubrication (EST2 = .46; P = .013). The intervention group reported more improvement over time in sexual pleasure (EST1 = .32 and EST2 = .62; P = .001), less discomfort during sex (EST1 = .49 and EST2 = .66; P = .001), and less sexual distress (EST2 = .59; P = .002) compared with the control group. The intervention group reported greater improvement in body image (EST2 = .45; P = .009) and fewer menopausal symptoms (EST1 = .39; P = .007) than the control group. No significant effects were observed for orgasmic function, sexual satisfaction, intercourse frequency, relationship intimacy, marital functioning, psychological distress, or health-related quality of life. Conclusion Internet-based CBT has salutary effects on sexual functioning, body image, and menopausal symptoms in BCSs with a sexual dysfunction.

Predicting pregnancy outcomes using longitudinal information: a penalized splines mixed-effects model approach.

We propose a semiparametric nonlinear mixed-effects model (SNMM) using penalized splines to classify longitudinal data and improve the prediction of a binary outcome. The work is motivated by a study in which different hormone levels were measured during the early stages of pregnancy, and the challenge is using this information to predict normal versus abnormal pregnancy outcomes. The aim of this paper is to compare models and estimation strategies on the basis of alternative formulations of SNMMs depending on the characteristics of the data set under consideration. For our motivating example, we address the classification problem using a particular case of the SNMM in which the parameter space has a finite dimensional component (fixed effects and variance components) and an infinite dimensional component (unknown function) that need to be estimated. The nonparametric component of the model is estimated using penalized splines. For the parametric component, we compare the advantages of using random effects versus direct modeling of the correlation structure of the errors. Numerical studies show that our approach improves over other existing methods for the analysis of this type of data. Furthermore, the results obtained using our method support the idea that explicit modeling of the serial correlation of the error term improves the prediction accuracy with respect to a model with random effects, but independent errors. Copyright © 2017 John Wiley & Sons, Ltd.

Population Pharmacokinetics of Darbepoetin in Infants Following Single Intravenous and Subcutaneous Dosing

Darbepoetin alfa (Darbe) is a hyperglycosylated analogue of recombinant human erythropoietin (Epo). The aim of this study was to develop a population pharmacokinetic model for Darbe following intravenous (i.v.) and subcutaneous (s.c.) administration to infants. Data from 2 infant clinical studies (a single i.v. dose study following a 4 μg/kg dose of Darbe, and a single s.c. dose study following 1 μg/kg or 4 μg/kg dose of Darbe) were combined and analyzed simultaneously using nonlinear mixed-effect modeling approach. Darbe population pharmacokinetics was well described by a 2-compartment model with first-order elimination. The covariate analysis identified significant impact of gender on clearance and bodyweight on volume of distribution. The clearance of Darbe was estimated to be 0.050 L/h/kg in male infants and 0.031 L/h/kg in female infants. The predicted population mean value of Vp is 0.84 L/kg, which is associated with the subject’s bodyweight (p < 0.05). Following s.c. administration, the estimated absorption rate (i.e., ka) of Darbe was 0.062 L/h. The model provides a suitable starting point for the development of further pharmacokinetic-pharmacodynamic models in infants in a variety of disease settings. Because the covariate-pharmacokinetic parameter relationships were identified in only 22 infants, further investigation with larger sample size is warranted.

Model performance of tree height-diameter relationships in the central Congo Basin

Tree heights in the central Congo Basin are overestimated using best-available height-diameter models. These errors are propagated into the estimation of aboveground biomass and canopy height, causing significant bias when used for calibration of remote sensing products in this region. Tree height-diameter models are important components of estimating aboveground biomass (AGB) and calibrating remote sensing products in tropical forests. For a data-poor area of the central Congo Basin, we quantified height-diameter model performance of local, regional and pan-tropical models for their use in estimating AGB and canopy height. At three old-growth forest sites, we assessed the bias introduced in height estimation by regional and pan-tropical height-diameter models. We developed an optimal local model with site-level randomizations accounted for by using a mixed-effects modeling approach. We quantified the error propagation of modeled heights for estimating AGB and canopy height. Regional and pan-tropical height-diameter models produced a significant overestimation in tree height, propagating into significant overestimations of AGB and Lorey’s height. The pan-tropical model accounting for climatic drivers performed better than the regional models. We present a local height-diameter model which produced nonsignificant errors for AGB and canopy height estimations at our study area. The application of general models at our study area introduced bias in tree height estimations and the derived stand-level variables. Improved delimitation of regions in tropical Africa with similar forest structure is needed to produce models fit for calibrating remote sensing products.

Risk for microbial keratitis: Comparative metaanalysis of contact lens wearers and post-laser in situ keratomileusis patients

To compare the risk for microbial keratitis in contact lens wearers stratified by wear schedule with the risk after laser in situ keratomileusis (LASIK). Hamilton Eye Institute and Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, Tennessee, USA. Comparative metaanalysis and literature review. An extensive literature search was performed in the PubMed database between December 2014 and July 2015. This was followed by a metaanalysis using a mixed-effects modeling approach. After 1year of daily soft contact lens wear, there were fewer microbialkeratitis cases than after LASIK, or approximately 2cases fewer cases per 10 000 (P=.0609). If LASIK were assumed to have essentially a 1-time risk for microbial keratitis, 5years of extrapolation would yield 11 more cases per 10 000 with daily soft contact lens wear than with LASIK, or approximately 3 times as many cases (P<.0001). The extended use of soft contact lenses led to 12 more cases at 1year than LASIK,or approximately 3 times as many cases (P<.0001), and 81 more cases at 5years (P<.0001). When incorporating an estimated 10% retreatment rate for LASIK, these results changed very little. Microbial keratitis is a relatively rare complication associated with contact lens use and LASIK postoperatively. The risk for microbial keratitis was similar between patients using contactlenses for 1year compared with LASIK. Over time, the risk for microbial keratitis was higher for contact lens use than for LASIK, specifically with extended-wear lenses.

Height-Diameter Model for Managed Even-aged Stands of Ponderosa Pine for the Western United States Using Hierarchical Nonlinear Mixed-Effects Model

Background: A regional individual-tree Height-Diameter (H-D) model was developed for ponderosa pine (P. ponderosa var. ponderosa and var. scopulorum), for the western United States. The dataset came from long-term permanent research plots in even-aged pure stands, both planted and natural on sites capable of the productivity estimated by Meyer [Meyer, W.H., 1938. Yield of Even-Aged Stands of Ponderosa Pine. USDA Technical Bulletin 630]. The database used a common study plan. The study plan divided the range of ponderosa pine trees into five provinces, with installations in Arizona (AZ), northern California (CA), Oregon (OR), Washington (WA), Montana (MT), and South Dakota (SD), USA. Regional H-D models exist for ponderosa pine. However, the study plans, the data collection and the analysis procedures used in developing the models differ. Consequently, comparisons of growth responses that may be due to geographic variation of the species are not possible. Objective: 1) develop a single regional H-D model for ponderosa pine trees that can provide useful guidelines for a variety of management objectives throughout the species range; 2) determine if inclusion of plot-specific auxiliary variables improves prediction accuracy of regional H-D models. Methodology: The dataset consisted of 305 plots and 29,449 trees. The study used 8208 trees that had both height and diameter measurements. The dataset has repeated measurements, which makes the measurements correlated. Additionally, the dataset has location effects and hierarchical structure; consequently, it violated the fundamental regression assumption of independent observations. Nonlinear Mixed-Effects Model (NLMM) approach provided an excellent solution. Specifically, NLMM allows parameter vectors to vary from plot to plot and variance components are simultaneously broken down into a) fixed-effect components that describe the shape of the typical growth curve over the entire population, b) random-effect components that enables the curve to capture the plot-specific and other unit-specific characteristics of the growth pattern. Further, NLMM allows the explicit incorporation of the hierarchical structure of the dataset. Finally, the inclusion of plot-specific auxiliary variables individualized the curve for each plot and location. Conclusions: The Chapman-Richards model form provided the best result. The results demonstrated that irrespective of geographic location, a regional H-D Model with variance components and plot-specific auxiliary variables that individualized the curve to capture the sitespecific, plot-specific, and other unit-specific characteristics of the growth pattern decisively outperformed regional H-D Model with variance components but without plot-specific auxiliary variables. Consequently, the model developed herein should enhance comparisons of H-D relationships that may be due to geographic variation of the species throughout the range of ponderosa pine trees. Therefore, it would provide forest managers and researchers with useful guidelines for a variety of management objectives at the regional scale.

Taper equations based on nonlinear mixed effect modeling approach for Pinus nigra in Çank&amp;#305;r&amp;#305; forests

In this study, statistical nonlinear mixed effect models were used to model taper of individual trees in Pinus nigra stands distributed within the Cankiri Forests. The data from 210 trees that were felled from Pinus nigra stands were used in this study. Three tree taper equations were fitted and evaluated based on the sum square error (SSE), mean square error (MSE), root mean square error (RMSE) and the adjusted coefficient of determination (R²adj). The Jiang et al.'s equation was found to produce the most satisfactory fits with the SSE (4125.7), MSE (2.1771), RMSE (1.4755) and (0.976). The stem taper equation of Jiang et al. was used within the scope of mixed-effect model structures that involved both random and constant effect parameters. The nonlinear mixed-effect modeling approach for the stem taper equation of Jiang et al. with SSE (3254.8), MSE (1.71759), RMSE (1.3119) provided much better fitting and precise predictions than those produced by the nonlinear fixed effect model structures for this model. Within various sampling scenarios including different numbers of the sub-sample trees based on some sampling strategies from the validation data set, the sampling scheme with three top diameter sub-sample in a tree produced the best predictive results (SSE = 313.5321, MSE = 0.8637 and RMSE = 0.9345) in relation to the fixed effect predictions.

Effect of Activated Charcoal on Rivaroxaban Complex Absorption.

To quantify the impact of activated charcoal (AC) on rivaroxaban exposure in healthy volunteers. This was an open-label study with an incomplete cross-over design of single-dose rivaroxaban (40mg) administered alone or with AC in 12 healthy volunteers. The study comprised three treatment periods in randomised sequence, one with rivaroxaban administered alone and two with AC given at 2, 5 or 8h post-dose. Rivaroxaban plasma concentration was measured in blood samples drawn at 16 time points. The pharmacokinetic model of rivaroxaban alone or with AC administration was built using a non-linear mixed-effect modelling approach. The pharmacokinetic model was based on a one-compartment model with an absorption rate described by the sum of three inverse Gaussian densities to reproduce multiphasic and prolonged absorption. The inclusion in the model of each AC administration schedule significantly improved objective function value. AC reduced the area under the rivaroxaban concentration-time curve by 43% when administered 2 h post-dose, by 31% when administered 5h post-dose and by 29% when administered 8h post-dose. Based on the estimated pharmacokinetic model, simulations suggested that AC might have an impact even after 8h post-dose. AC administration significantly reduces exposure to rivaroxaban even if AC is administered 8h after rivaroxaban. These results suggest that AC could be used in rivaroxaban overdose and accidental ingestion to antagonise absorption. CLINICALTRIAL. NCT02657512.

A climate-sensitive aboveground biomass model for three larch species in northeastern and northern China

A climate-sensitive aboveground biomass model developed by combining a nonlinear mixed-effects model and dummy variable approach led to higher prediction accuracy of biomass than those without climatic variables for three larch species. As native species and being widely distributed in northeastern and northern China, larch forests play a pivotal role in maintaining forest ecosystem functions and mitigation of carbon concentration at the atmosphere. However, the spatial sensitivity of growing and aboveground biomass (AGB) of larch species to climate change is not known. In this study, a climate-sensitive AGB model was developed by combining nonlinear mixed-effects modeling and a dummy variable approach to account for the spatial sensitivity of AGB of three larch species including Dahurian larch (Larix gmelinii (Rupr.) Kuzen.), Korean larch (Larix olgensis Henry.) and Prince Rupprecht larch (Larix principis rupprechtii Mayr.) to climate change in northeastern and northern China. We examined the AGB values of 256 larch trees growing in five secondary climate zones: mid-temperature humid climatic zone, mid-temperature sub-humid climatic zone, mid-temperature semi-arid climatic zone, cool temperature humid climatic zone and warm temperature sub-humid climatic zone in northeastern and northern China. The results showed that the long-term averages of growing season temperature and total growing season precipitation, and the mean temperature and precipitation of wettest quarter, had significant (α = 0.05) effects on AGB. The prediction accuracy of the developed model was much higher than that of the model at the population average level and its base model. Excessive rain and high mean temperature during the growing season increased the AGB values of larch trees, while abundant precipitation and high mean temperature in the wettest quarter led to the decrease of AGB. The AGB of the larch species from the mid-temperature semi-arid climatic zone had the greatest values, which indicated that climate conditions were more favorable in this zone than in the other four secondary climate zones. It is expected that the findings from this study can be combined with the knowledge of adaptive management to reduce the risks and uncertainties associated with forest management decisions.

CERAMIC: Case-Control Association Testing in Samples with Related Individuals, Based on Retrospective Mixed Model Analysis with Adjustment for Covariates

We consider the problem of genetic association testing of a binary trait in a sample that contains related individuals, where we adjust for relevant covariates and allow for missing data. We propose CERAMIC, an estimating equation approach that can be viewed as a hybrid of logistic regression and linear mixed-effects model (LMM) approaches. CERAMIC extends the recently proposed CARAT method to allow samples with related individuals and to incorporate partially missing data. In simulations, we show that CERAMIC outperforms existing LMM and generalized LMM approaches, maintaining high power and correct type 1 error across a wider range of scenarios. CERAMIC results in a particularly large power increase over existing methods when the sample includes related individuals with some missing data (e.g., when some individuals with phenotype and covariate information have missing genotype), because CERAMIC is able to make use of the relationship information to incorporate partially missing data in the analysis while correcting for dependence. Because CERAMIC is based on a retrospective analysis, it is robust to misspecification of the phenotype model, resulting in better control of type 1 error and higher power than that of prospective methods, such as GMMAT, when the phenotype model is misspecified. CERAMIC is computationally efficient for genomewide analysis in samples of related individuals of almost any configuration, including small families, unrelated individuals and even large, complex pedigrees. We apply CERAMIC to data on type 2 diabetes (T2D) from the Framingham Heart Study. In a genome scan, 9 of the 10 smallest CERAMIC p-values occur in or near either known T2D susceptibility loci or plausible candidates, verifying that CERAMIC is able to home in on the important loci in a genome scan.

Theophylline: a review of population pharmacokinetic analyses.

Numerous population pharmacokinetic studies of theophylline have been conducted in paediatric and adult patients. The purpose of this review was to summarize the published studies concerning population pharmacokinetics of theophylline in patients of different ages and discuss factors that might cause the large variability in the pharmacokinetics of theophylline. A literature search was conducted in PubMed using the following keywords: 'theophylline', 'population pharmacokinetic(s)' and 'nonlinear mixed effect model'. Additionally, the relevant references listed in the retrieved articles were manually reviewed. All of the studies that reported the population pharmacokinetics of theophylline in humans were included in this review. However, articles were excluded if they were not written in English. Sixteen articles were included in this review. Among them, 11 were conducted on paediatric patients, and five were conducted on adults. A one-compartment model with first-order elimination was employed in most of the included articles. A nonlinear mixed effect modelling approach (NONMEM) was the most commonly used software to develop a population pharmacokinetic model. Body weight and age (post-conceptional age and post-natal age) were the most important factors associated with the clearance (CL) of theophylline in paediatric patients. Body weight (ideal body weight and lean body mass), age and smoking status were most frequently used to estimate the CL of theophylline in adults. The median (range) estimate values of CL for paediatric and adult patients were 0·062 (0·0056-0·0949) L/h/kg and 0·053 (0·0493-0·0517) L/h/kg, respectively. The median values of the interindividual variability of CL were 33·5% in adults and 25·8% in paediatric patients. The mean values of the residual variability were 21% in paediatric patients and 14·3% in adults. This review concludes that body weight and age were the most important factors associated with the clearance of theophylline in paediatric patients. Body weight, age and smoking were most frequently used to estimate the clearance of theophylline in adults. Future studies are warranted to detect the influence of new factors, such as cytochrome P450 (CYP) 1A2 gene polymorphisms, on the pharmacokinetics of theophylline because some pharmacokinetic variability was not fully explained.

Bayesian inference on partially linear mixed-effects joint models for longitudinal data with multiple features

The relationship between viral load and CD4 cell count is one of the interesting questions in AIDS research. Statistical models are powerful tools for clarifying this important problem. Partially linear mixed-effects (PLME) model which accounts for the unknown function of time effect is one of the important models for this purpose. Meanwhile, the mixed-effects modeling approach is suitable for the longitudinal data analysis. However, the complex process of data collection in clinical trials has made it impossible to rely on one particular model to address the issues. Asymmetric distribution, measurement error and left censoring are features commonly arisen in longitudinal studies. It is crucial to take into account these features in the modeling process to achieve reliable estimation and valid conclusion. In this article, we establish a joint model that accounts for all these features in the framework of PLME models. A Bayesian inferential procedure is proposed to estimate parameters in the joint model. A real data example is analyzed to demonstrate the proposed modeling approach for inference and the results are reported by comparing various scenarios-based models.

Separating the Association Between Inhibitory Control and Substance Use Prevalence Versus Quantity During Adolescence: A Hurdle Mixed-Effects Model Approach

ABSTRACTBackground: Inhibitory control is a critical component to the self-regulation of affect and behavior. Research consistently demonstrates negative associations between inhibitory control and several problem behaviors including substance misuse during early adolescence. However, analytic approaches previously used have often applied ordinary least squares (OLS) regression to non-normal count data with an excessive number of zeros (i.e., never users), violating several model assumptions. Further, OLS regression fails to model effects of the independent variable, separately, for both prevalence and quantity of use. Objective: The study objective was to simultaneously model associations between inhibitory control and both past 30-day prevalence and amount of cigarette and marijuana use. It was hypothesized that when doing so, inhibitory control would be significantly associated with prevalence, but not quantity of use. Method: Hurdle Mixed-effects Models (HMM) were used for hypothesis testing on data collected from 3,383, 9th grade adolescents (Mage = 14.08 years). Results: Results confirmed hypotheses, demonstrating that although significant bivariate associations between inhibitory control and quantity of cigarette and marijuana use existed, HMM analyses established that the associations were more precisely specific to past 30-day prevalence, and not quantity of use. Conclusion: Results from a HMM approach contribute to a more comprehensive and nuanced understanding of which characteristics of cigarette and marijuana use are associated with inhibitory control during early adolescence.

Testing differentially expressed genes in dose-response studies and with ordinal phenotypes.

When testing for differentially expressed genes between more than two groups, the groups are often defined by dose levels in dose-response experiments or ordinal phenotypes, such as disease stages. We discuss the potential of a new approach that uses the levels' ordering without making any structural assumptions, such as monotonicity, by testing for zero variance components in a mixed models framework. Since the mixed effects model approach borrows strength across doses/levels, the test proposed can also be applied when the number of dose levels/phenotypes is large and/or the number of subjects per group is small. We illustrate the new test in simulation studies and on several publicly available datasets and compare it to alternative testing procedures. All tests considered are implemented in R and are publicly available. The new approach offers a very fast and powerful way to test for differentially expressed genes between ordered groups without making restrictive assumptions with respect to the true relationship between factor levels and response.

Individual tree crown width models for Norway spruce and European beech in Czech Republic

Both spatially explicit and spatially non-explicit individual tree crown width models were developed for Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) using a large dataset from fully stem-mapped permanent research plots (PRPs) located in various parts of the Czech Republic. A number of tree and stand characteristics were evaluated for their potential contributions to the description of the crown width variations. In addition to diameter at breast height (DBH), other significant predictor variables identified for crown width models are dominant height (HDOM), height-diameter ratio (tree slenderness coefficient), height to crown base, DBH sum of all tree species per PRP and proportion of DBH sum for a species of the interest (spatially non-explicit competition measures), and Hegyi’s index (spatially explicit competition measure). Among various base functions evaluated, a simple power function was chosen to expand through the integration of tree and stand variables. The PRP-level random effects were also included using mixed effect modeling approach. Both spatially explicit and spatially non-explicit models and their mixed effect versions described large parts of the crown width variations [R2adj=0.76–0.78 (Norway spruce), 0.70–0.73 (European beech)] without significant residual trends. For both species, spatially explicit mixed effect model described larger part of the crown width variations than its spatially non-explicit mixed effect counterpart. The models showed that after DBH, height-diameter ratio for Norway spruce and HDOM for European beech showed the largest contribution to the models. The crown width increased with increasing dominant height, but decreased with increasing height-diameter ratio, height to crown base, and competition among the trees within a stand. For both species, spatially explicit competition exhibited significantly larger effect on crown width than spatially non-explicit ones. This suggests that spatially explicit models can be more appropriate for description of the individual tree growth dynamics than spatially non-explicit ones. However, because of a little difference between the fit statistics of spatially explicit and spatially non-explicit models, the later models can be applied for precise predictions of crown width as they do not require spatially explicit competition measures, which are computationally complex and difficult.