Model of mixed effects of height dependence on tree diameters in pine stands

Основными исходными данными для определения запаса служат результаты обмеров диаметров и высот деревьев. Но обмеры диаметров деревьев на высоте груди выполнить намного проще, чем обмеры высот, поэтому ограничиваются замерами высот 15–25 деревьев. Цель исследования – по материалам измерения модельных деревьев в сосновых древостоях выбрать наиболее адекватную простую модель, которая передает зависимость между высотой деревьев и диаметром на высоте груди. Объектом исследования послужили сосновые древостои искусственного происхождения на постоянных пробных площадях в Лесной опытной даче Российского государственного агарного университета – МСХА имени К.А. Тимирязева. В работе используются данные обмеров деревьев на 17 постоянных пробных площадях с 1934 по 2005 гг. Возраст древостоев на момент проведения измерений от 50 до 125 лет. По итогам проведения 77 перечетов массив данных составил 1157 наблюдений. И модель фиксированных эффектов, и модель смешанных эффектов адекватно описали зависимость между высотами и диаметрами деревьев в культурах сосны. Но, как и ожидалось, первая модель имеет худшие значения метрик качества по сравнению со второй. Модель со смешанными эффектами более точно предсказывает значения высот по сравнению с моделью фиксированных эффектов. Недостающие значения высот большого количества деревьев на участке можно вычислить более точно с помощью модели смешанных эффектов, а не применения модели фиксированных эффектов или использования только фиксированной части (средний отклик) модели смешанных эффектов. Применение разработанной модели должно ограничиваться только в тех условиях, к которым относятся экспериментальные материалы The main data for the stock of research results is the diameter of measurements and heights of trees. But measurements of the diameter at breast height are much easier to perform than measurements of heights, therefore, they are limited to measuring the heights of 15–25 trees. The aim of the study is to select the most adequate simple model based on the measurements of model trees in pine antiquities, which conveys the relationship between the height of trees and the diameter at breast height. The object of the study was pine stands of artificial origin on permanent test plots in the Forest Experimental Station Russian State Agararian University – Moscow Timiriazev Agricultural Academy. The work uses data from tree measurements on 17 permanent sample plots from 1934 to 2005. The age of the stands at the time of measurements was from 50 to 125 years. As a result of 77 enumerations, the data array amounted to 1157 observations. Both the fixed effects model and the mixed effects model adequately describe the relationship between heights and diameters of trees in pine stumps. But, as expected, the first model has worse quality metrics than the second. The mixed effects model more accurately predicts heights from the fixed effects model. The missing heights of a large number of trees on a site can be calculated accurately using mixed effects models, rather than using fixed effects models or using only a fixed portion (mean response) of the mixed effects model. The application of the developed model should be limited only in those conditions to which the experimental materials are applied.

Modelling the Tree Height, Crown Base Height, and Effective Crown Height of Pinus koraiensis Plantations Based on Knot Analysis

Taking 1735 Pinus koraiensis knots in Mengjiagang Forest Farm plantations in Jiamusi City, Heilongjiang Province as the research object, a dynamic tree height, effective crown height, and crown base height growth model was developed using 349 screened knots. The Richards equation was selected as the basic model to develop a crown base height and effective crown height nonlinear mixed-effects model considering random tree-level effects. Model parameters were estimated with the non-liner mixed effect model (NLMIXED) Statistical Analysis System (SAS) module. The akaike information criterion (AIC), bayesian information criterion (BIC), −2 Log likelihood (−2LL), adjusted coefficient (Ra2), root mean square error (RMSE), and residual squared sum (RSS) values were used for the optimal model selection and performance evaluation. When tested with independent sample data, the mixed-effects model tree effects-considering outperformed the traditional model regarding their goodness of fit and validation; the two-parameter mixed-effects model outperformed the one-parameter model. Pinus koraiensis pruning times and intensities were calculated using the developed model. The difference between the effective crown and crown base heights was 1.01 m at the 15th year; thus, artificial pruning could occur. Initial pruning was performed with a 1.01 m intensity in the 15th year. Five pruning were required throughout the young forest period; the average pruning intensity was 1.46 m. The pruning interval did not differ extensively in the half-mature forest period, while the intensity decreased significantly. The final pruning intensity was only 0.34 m.

A state-space approach for longitudinal outcomes: An application to neuropsychological outcomes

Longitudinal assessments are crucial in evaluating the disease state and trajectory in patients with neurodegenerative diseases. Neuropsychological outcomes measured over time often have a non-linear trajectory with autocorrelated residuals and a skewed distribution. We propose the adjusted local linear trend model, an extended state-space model in lieu of the commonly used linear mixed-effects model in modeling longitudinal neuropsychological outcomes. Our contributed model has the capability to utilize information from the stochasticity of the data while accounting for subject-specific trajectories with the inclusion of covariates and unequally spaced time intervals. The first step of model fitting involves a likelihood maximization step to estimate the unknown variances in the model before parsing these values into the Kalman filter and Kalman smoother recursive algorithms. Results from simulation studies showed that the adjusted local linear trend model is able to attain lower bias, lower standard errors, and high power, particularly in short longitudinal studies with equally spaced time intervals, as compared to the linear mixed-effects model. The adjusted local linear trend model also outperforms the linear mixed-effects model when data is missing completely at random, missing at random, and, in certain cases, even in data with missing not at random.

Use of modified composite index of anthropometric failure and MUAC-for-age to assess prevalence of malnutrition among school-age children and adolescents involved in the school feeding program in Addis Ababa, Ethiopia

Background Malnutrition hampers educational performance of schoolchildren coming from low-income families. School feeding program was, thus, launched in public primary schools in Addis Ababa very recently. It is, thus, important to measure the initial nutritional status of participating students to see the effect of the program on their nutritional wellbeing. Methods The first-round survey was made at the initiation of the program. A multi-stage stratified sampling from 50 schools located in the ten sub cities of Addis Ababa yielded 4500 children and adolescents of ages five to 19 years. Data was collected on age, height, weight and MUAC of the schoolchildren. Nutritional status was evaluated using conventional anthropometric indicators, modified Composite Index of Anthropometric Failure (mCIAF), and MUAC-for-age. Receiver Operating Characteristic (ROC) curve was used to examine classification of malnourishment by MUAC-for-age versus BMI-for-age and mCIAF versus MUAC-for-age. Multilevel mixed effects model was applied to investigate variations in the prevalence of malnutrition across sub cities. Findings The area under the ROC curves (AUC) for MUAC-for-age against BMI-for-age z-scores was 0.68 and that of mCIAF against MUAC-for-age was 0.70, respectively, indicating an overall better classification of malnourishment. Mixed effects model showed significant variations in nutritional status of schoolchildren across sub cities. Conventional measures showed that prevalence of stunting, thinness, or underweight among the sample children and adolescents was 23.4, 18.4, and 16.5%, respectively. Assessment by mCIAF, instead, showed a higher prevalence of overall malnutrition (43.4%). MUAC-for-age indicated an acute malnutrition measurement of 33.4%. Significant differences (p < 0.0001) in nutritional status were seen between boys and girls, and among age groups as measured by mCIAF. Interpretation Conventional measures of nutritional status undermined level of malnutrition. Instead, mCIAF and MUAC-for-age gave higher estimates of the magnitude of the existing prevalence of malnutrition among the school children and adolescents.

Heterogeneous Heterogeneity by Default: Testing Categorical Moderators in Random-effects Meta-Analysis

Categorical moderators are often included in mixed-effects meta-analysis to explain heterogeneity in effect sizes. An assumption in tests of moderator effects is that of a constant between-study variance across all levels of the moderator. Although it rarely receives serious thought, there can be drastic ramifications to upholding this assumption. We propose that researchers should instead assume unequal between-study variances by default. To achieve this, we suggest using a mixed-effects location-scale model (MELSM) to allow group-specific estimates for the between-study variances. In two extensive simulation studies, we show that in terms of Type I error and statistical power, nearly nothing is lost by using the MELSM for moderator tests, but there can be serious costs when a mixed-effects model with equal variances is used. Most notably, in scenarios with balanced sample sizes or equal between-study variance, the Type I error and power rates are nearly identical between the mixed-effects model and the MELSM. On the other hand, with imbalanced sample sizes and unequal variances, the Type I error rate under the mixed-effects model can be grossly inflated or overly conservative, whereas the MELSM excellently controlled the Type I error across all scenarios. With respect to power, the MELSM had comparable or higher power than the mixed-effects model in all conditions where the latter produced valid (i.e., not inflated) Type 1 error rates. Altogether, our results strongly support that assuming unequal between-study variances is preferred as a default strategy when testing categorical moderators

Beyond personal factors: Multilevel determinants of childhood stunting in Indonesia

Background Stunting is still a major public health problem in low- and middle-income countries, including Indonesia. Previous studies have reported the complexities associated with understanding the determinants of stunting. This study aimed to examine the household-, subdistrict- and province-level determinants of stunting in Indonesia using a multilevel hierarchical mixed effects model. Methods We analyzed data for 8045 children taken from the 2007 and 2014 waves of the Indonesian Family and Life Surveys (IFLS). We included individual-, family-/household- and community-level variables in the analyses. A multilevel mixed effects model was employed to take into account the hierarchical structure of the data. Moreover, the model captured the effect of unobserved household-, subdistrict- and province-level characteristics on the probability of children being stunted. Results Our findings showed that the odds of childhood stunting vary significantly not only by individual child- and household-level characteristics but also by province- and subdistrict-level characteristics. Among the child-level covariates included in our model, dietary habits, neonatal weight, a history of infection, and sex significantly affected the risk of stunting. Household wealth status and parental education are significant household-level covariates associated with a higher risk of stunting. Finally, the risk of stunting is higher for children living in communities without access to water, sanitation and hygiene. Conclusions Stunting is associated with not only child-level characteristics but also family- and community-level characteristics. Hence, interventions to reduce stunting should also take into account family and community characteristics to achieve effective outcomes.

Hispanic/Latino‐Serving Hospitals Provide Less Targeted Temperature Management Following Out‐of‐Hospital Cardiac Arrest

Background Variation exists in outcomes following out‐of‐hospital cardiac arrest (OHCA), but whether racial and ethnic disparities exist in post‐arrest provision of targeted temperature management (TTM) is unknown. Methods and Results We performed a retrospective analysis of a prospectively collected cohort of patients who survived to admission following OHCA from the Cardiac Arrest Registry to Enhance Survival, whose catchment area represents ~50% of the United States from 2013‐2019. Our primary exposure was race/ethnicity and primary outcome was utilization of TTM. We built a mixed‐effects model with both state of arrest and admitting hospital modeled as random intercepts to account for clustering. Among 96,695 patients (24.6% Black, 8.0% Hispanic/Latino, 63.4% White), a smaller percentage of Hispanic/Latino patients received TTM than Black or White patients (37.5% vs. 45.0 % vs 43.3%, P < .001) following OHCA. In the mixed‐effects model, Black patients (Odds Ratio [OR] 1.153, 95% Confidence Interval [CI] 1.102‐1.207, P < .001) and Hispanic/Latino patients (OR 1.086, 95% CI 1.017‐1.159, P < .001) were slightly more likely to receive TTM compared to White patients, perhaps due to worse admission neurological status. We did find community level disparity as Hispanic/Latino‐serving hospitals (defined as the top decile of hospitals that cared for the highest proportion of Hispanic/Latino patients) provided less TTM (OR 0.587, 95% CI 0.474 to 0.742, P < .001). Conclusions Reassuringly, we did not find evidence of intrahospital or interpersonal racial or ethnic disparity in the provision of TTM. However, we did find inter‐hospital, community level disparity. Hispanic/Latino‐serving hospitals provided less guideline‐recommended TTM after OHCA.