Evaluation of population-averaged and subject-specific approaches for modeling the dominant or codominant height of lodgepole pine trees

2009 ◽  
Vol 39 (6) ◽  
pp. 1148-1158 ◽  
Author(s):  
Shawn X. Meng ◽  
Shongming Huang ◽  
Yuqing Yang ◽  
Guillermo Trincado ◽  
Curtis L. VanderSchaaf
Keyword(s):  
Fixed Effects ◽  
Lodgepole Pine ◽  
Logistic Function ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Prediction Errors ◽  
Validation Data ◽  
Data Set ◽  
Subject Specific ◽  
Better Than

Population-averaged (PA) and subject-specific (SS) approaches for modeling the height of dominant or codominant lodgepole pine ( Pinus contorta Dougl. ex Loud.) trees were evaluated using six candidate models derived from the Chapman–Richards and logistic functions. The true PA response obtained from separate fits of the models was compared with the typical mean (TM) response computed using only the fixed-effects parameters of the mixed-effects models. Results showed that the TM response had higher prediction errors than the PA response, suggesting that a true PA response and not the TM response is needed to reflect the overall mean response of the model. The SS approach produced improved height predictions relative to the PA approach when evaluated using independent validation data. In addition, the logistic performed better than the Chapman–Richards function, regardless of whether the SS or PA approach was applied. Among the candidate models, the logistic function with the inclusion of site index gave the most accurate predictions. Three scenarios of calibrating the mixed-effects models on the validation data set were compared. The SS predictions obtained using only one premeasured observation per subject were poorer than those using all observations, but they were still generally better than PA predictions.

scholarly journals Comparison of Fixed- and Mixed-effects Approaches to Taper Modeling for Scots Pine in West Poland

Forests ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 975 ◽  
Author(s):  
Karol Bronisz ◽  
Michał Zasada
Keyword(s):  
Random Effects ◽  
Scots Pine ◽  
Fixed Effects ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Fixed Effects Model ◽  
Validation Data ◽  
Data Set ◽  
Taper Model ◽  
Model Approach

Diameter measurements along the stem, which are the basis for taper models, usually have a hierarchical structure. Mixed-effects models, where fixed and random effects are distinguished, are a possible solution for this type of data. However, in order to fully absorb the potential of this method, random effects prediction, which requires additional measurements (diameter along stem), is recommended. This article presents a comparison of various fitting methods (mixed- and fixed-effects model approaches) of the variable-exponent taper model created by Kozak for determining the outside bark diameter along the stem and predicting the tree volume of Scots pine trees in west Poland. During the analysis, it was assumed that no additional measured data were available for practical use; therefore, for the mixed-effects model approach, fixed effects prediction without random effects was applied. Both fitting strategies were compared based on modeling and an independent validation data set. The comparison of mixed- and fixed-effects fitting strategies for the diameter along the stem indicated that the taper model fitted using the mixed-effects model approach better fit the data. Moreover, the error rate for the total tree volume prediction for the independent data set was lower for the mixed-effects model solution than for the fixed-effects one.

Modeling the Effect of Prior Sublethal Thermal History on the Thermal Inactivation Rate of Salmonella in Ground Turkey

2008 ◽  
Vol 71 (2) ◽  
pp. 279-285 ◽  
Author(s):  
M. J. STASIEWICZ ◽  
B. P. MARKS ◽  
A. ORTA-RAMIREZ ◽  
D. M. SMITH
Keyword(s):  
Thermal History ◽  
Thermal Inactivation ◽  
Mean Squared Error ◽  
Inactivation Rate ◽  
Prediction Errors ◽  
Independent Data ◽  
Validation Data ◽  
Data Set ◽  
Dependent Model ◽  
Path Dependent

Traditional models for predicting the thermal inactivation rate of bacteria are state dependent, considering only the current state of the product. In this study, the potential for previous sublethal thermal history to increase the thermotolerance of Salmonella in ground turkey was determined, a path-dependent model for thermal inactivation was developed, and the path-dependent predictions were tested against independent data. Weibull-Arrhenius parameters for Salmonella inactivation in ground turkey thigh were determined via isothermal tests at 55, 58, 61, and 63°C. Two sets of nonisothermal heating tests also were conducted. The first included five linear heating rates (0.4, 0.9, 1.7, 3.5, and 7.0 K/min) and three holding temperatures (55, 58, and 61°C); the second also included sublethal holding periods at 40, 45, and 50°C. When the standard Weibull-Arrhenius model was applied to the nonisothermal validation data sets, the root mean squared error of prediction was 2.5 log CFU/g, with fail-dangerous residuals as large as 4.7 log CFU/g when applied to the complete nonisothermal data set. However, by using a modified path-dependent model for inactivation, the prediction errors for independent data were reduced by 56%. Under actual thermal processing conditions, use of the path-dependant model would reduce error in thermal lethality predictions for slowly cooked products.

scholarly journals Perceiving education from Facebook profile pictures

2019 ◽  
Vol 22 (3) ◽  
pp. 550-570 ◽  
Author(s):  
Michael V. Reiss ◽  
Milena Tsvetkova
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Educational Background ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Outdoor Activities ◽  
Online Study ◽  
The Social ◽  
Profile Pictures ◽  
Better Than

Our upbringing and education influence not only how we present and distinguish ourselves in the social world but also how we perceive others. We apply this central sociological idea to the social media context. We conduct a large-scale online study to investigate whether observers can correctly guess the education of others from their Facebook profile pictures. Using the binomial test and cross-classified mixed-effects models, we show that observers can assess the education of depicted persons better than chance, especially when they share the same educational background and have experience with the social media. We also find that posting pictures of outdoor activities is a strong signal of having higher education, while professional photographs can obscure education signals. The findings expand our knowledge of social interaction and self-expression online and offer new insights for understanding social influence on social media.

Kernels for Longitudinal Data with Variable Sequence Length and Sampling Intervals

2011 ◽  
Vol 23 (9) ◽  
pp. 2390-2420 ◽  
Author(s):  
Zhengdong Lu ◽  
Todd K. Leen ◽  
Jeffrey Kaye
Keyword(s):  
Longitudinal Data ◽  
Cognitive Decline ◽  
Likelihood Ratio ◽  
Neuropsychological Tests ◽  
Motor Behavior ◽  
Generative Models ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Sequence Length ◽  
Better Than

We develop several kernel methods for classification of longitudinal data and apply them to detect cognitive decline in the elderly. We first develop mixed-effects models, a type of hierarchical empirical Bayes generative models, for the time series. After demonstrating their utility in likelihood ratio classifiers (and the improvement over standard regression models for such classifiers), we develop novel Fisher kernels based on mixture of mixed-effects models and use them in support vector machine classifiers. The hierarchical generative model allows us to handle variations in sequence length and sampling interval gracefully. We also give nonparametric kernels not based on generative models, but rather on the reproducing kernel Hilbert space. We apply the methods to detecting cognitive decline from longitudinal clinical data on motor and neuropsychological tests. The likelihood ratio classifiers based on the neuropsychological tests perform better than than classifiers based on the motor behavior. Discriminant classifiers performed better than likelihood ratio classifiers for the motor behavior tests.

scholarly journals Outcomes in Vaso-Occlusive Crisis Treatment in the Emergency Department Vs. Acute Care Observation Center

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 22-23
Author(s):  
Renee Cheng ◽  
Avani Singh ◽  
Xu Zhang ◽  
Priyanka Nasa ◽  
Jin Han ◽  
...  
Keyword(s):  
Emergency Department ◽  
Acute Care ◽  
Research Funding ◽  
Admission Rate ◽  
Pain Medication ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Data Set ◽  
Admission Rates ◽  
Significant Difference

I NTRODUCTION: Acute painful vaso-occlusive crises (VOC) are the leading cause of emergency department (ED) encounters and hospital admissions for those with sickle cell disease (SCD). For SCD patients, the goal of the sickle cell acute care observation unit (ACOU) at University of Illinois Health (UIH) is to improve patient outcomes by providing immediate care for an uncomplicated VOC. At our urban hospital which cares for more than 500 adult SCD patients, a considerable portion of SCD patients, despite having access to the ACOU, continue to present to the ED for treatment of an uncomplicated VOC. In order to help improve our current system, this study investigated outcomes in SCD patients who receive care for an uncomplicated VOC in the ACOU versus the ED at UIH. METHODS: By querying the electronic medical record, a retrospective study was conducted to analyze outcomes of encounters from the ACOU and ED at UIH between October 2019 and December 2019, specifically including SCD patients ≥18 years old who received morphine for treatment of an uncomplicated VOC. Encounters for complicated VOCs such as acute chest syndrome and stroke were excluded. Endpoints collected include time to first dose of morphine, total milligrams (mg) of IV morphine equivalents given, number of total morphine doses, admission rates, subsequent hospital length of stay, and 30-day inpatient admission rates. Time to the first dose (log transformed) and total dose in mg were analyzed by linear mixed effects models. The number of doses and hospitalization days were analyzed by negative binomial mixed effects model. Admissions and 30-day admissions were analyzed by logistic mixed effects models. These models adjusted for age, gender, and severe Hb genotype (HbSS or HbS beta0-thalassemia) and treated patient identity as random effect. P values were obtained from Wald- test. RESULTS: The ACOU data set contains 394 patient encounters for 79 patients with a median age of 33 years (interquartile range [IQR], 28-40), 71% female, and 73% with severe sickle genotypes. The ED data set contains 391 patient encounters for 128 patients with a median age of 30 years (IQR, 26-41), 53% female, and 74% with severe sickle genotypes. In the ACOU, the median time to first dose of morphine was 49 minutes (IQR, 39-60) compared to 107 minutes (IQR, 71-194) in the ED. The time to first dose was significantly longer in the ED compared to the ACOU (eβ=2.5, p <2×10-16). There was no significant difference in the total number of morphine doses received nor the total mg of morphine received between the two locations. Admission rate from ACOU was 6.6% compared to 53% from ED (OR=0.019, p=2x10-16). Of those admitted, the median number of hospitalization days from the ACOU was 4 days (IQR, 2.3-5.8) and 4 days (IQR, 2.0-6.5) from the ED. There was no significant difference in hospitalization days (p=0.6). The 30-day admission rate was 55% from the ACOU compared to 58% from the ED. 30-day admission rate however had strong intra-patient correlation (i.e., a patient was likely re-admitted multiple times): 44% of patients from the ACOU had admissions within 30 days of their ACOU visit compared to 32% from the ED. Controlling for the intra-patient correlation, ACOU visits had a higher 30-day admission rate than ED visit (OR=2.8, p=0.0015). DISCUSSION: SCD patients treated for an uncomplicated VOC at the sickle ACOU at UIH had a significantly shorter time to initial dose of IV pain medication. The wait time in the ED before first dose of IV pain medication received was more than double than those treated in the ACOU. Patients treated for an uncomplicated VOC in ACOU and ED had similar hospitalization days without a statistically significant difference. The 30-day admission rate to the inpatient setting was comparable for those treated in the ED versus the ACOU. However, given that only 6.6% of patients from the ACOU were admitted during the study period, this suggests that most patients who use both the ED and ACOU tend to be subsequently admitted from the ED. SCD patients may be presenting to the ED for treatment of VOC if capacity in the ACOU is exceeded or are presenting outside of hours of operation (currently 2 shifts Monday through Saturday). Therefore, improving access to our ACOU by increasing capacity and hours of operation may subsequently also lead to a decrease in time to first dose of medication and decrease in the overall 30-day admission rate. Disclosures Gordeuk: Imara: Research Funding; CSL Behring: Consultancy, Research Funding; Global Blood Therapeutics: Consultancy, Research Funding; Novartis: Consultancy; Ironwood: Research Funding.

Modelling and localizing a stem taper function for Pinus radiata in Spain

2015 ◽  
Vol 45 (6) ◽  
pp. 647-658 ◽  
Author(s):  
Manuel Arias-Rodil ◽  
Ulises Diéguez-Aranda ◽  
Francisco Rodríguez Puerta ◽  
Carlos Antonio López-Sánchez ◽  
Elena Canga Líbano ◽  
...  
Keyword(s):  
Random Effects ◽  
Pinus Radiata ◽  
Mixed Model ◽  
Mixed Effects ◽  
Stem Diameter ◽  
Mixed Effects Models ◽  
Stem Volume ◽  
Diameter Measurement ◽  
Data Set ◽  
Taper Function

The parsimonious taper function proposed by Riemer et al. (1995. Allg. Forst.- Jagdztg. 166(7): 144–147) was fitted for radiata pine (Pinus radiata D. Don) stems in Spain by using a nonlinear mixed modelling approach. Eight candidate models (all possible expansion combinations of the three fixed parameters with random effects) were assessed, and the mixed model with three random effects performed the best according to the goodness-of-fit statistics. An evaluation data set was used to assess the performance of these models in predicting stem diameter along the bole, as well as total stem volume. Four prediction approaches were compared: one subject (tree) specific (SS) and three population specific (ordinary least squares (OLS), mean (M), and population averaged (PA)). The SS responses for a tree were estimated from a prior stem diameter measurement available for that tree, whereas OLS, M, and PA were obtained from the fixed-effects model, from the fixed parameters of mixed-effects models, and by computing mean predictions from the mixed-effects models over the distribution of random effects, respectively. Prediction errors were greater for the M and PA responses than for the OLS response, and therefore, from the prediction point of view, the use of the mixed-effects models is not recommended when an additional stem diameter measurement is not available. The mixed model with three random effects was also selected as the best model for SS estimations. Measurement of an additional stem diameter at a relative tree height of approximately 0.5 provided the best calibrations for stem diameters along the bole and total stem volume predictions. The SS approach increased the flexibility and efficiency of the selected mixed-effects model for localized predictions and thus improved the overall predictive capacity of the base model.

scholarly journals Investigation of parametric and artificial neural network modeling approaches for total tree height prediction in cedar plantations

2020 ◽  
Author(s):  
Yasin Karatepe ◽  
Maria J. Diamantopoulou ◽  
Ramazan Özçelik ◽  
Zerrin Sürücü
Keyword(s):  
Mixed Effects ◽  
Parametric Modeling ◽  
Volume Estimation ◽  
Neural Network Modeling ◽  
Stem Height ◽  
Validation Data ◽  
Data Set ◽  
Prediction Ability ◽  
Height Prediction ◽  
Artificial Neural

Abstract Background: Height-diameter relationships are of critical importance in tree and stand volume estimation. Stand description, site quality determination and proper forest management decisions originate from reliable stem height predictions. Methods: In the context of this work, the prediction ability of the developed height-diameter models was investigated for cedar (Cedrus libani A. Rich.) plantations in Western Mediterranean Region of Turkey. Towards this direction, parametric modeling methods such as fixed-effects, generalized models, and mixed-effects were evaluated. Furthermore, in an effort to come up with the construction of more reliable stem-height prediction models, artificial neural networks were employed using two different modeling algorithms: the Levenberg-Marquardt and the resilient back-propagation. Results: Taking into account the prediction behavior of each respective modelling strategy while using a new validation data set, the mixed-effects model with calibration using 3 trees for each plot seems to be a reliable alternative to the rest standard modelling approaches given the evaluation statistics regarding the predictions of tree heights. Conclusion: Finally, as for providing the most reliable results as compared to the remaining, the resilient propagation algorithm showed its capability of providing more accurate predictions of the tree stem height and thus it can be a reliable alternative to pre-existing modelling methodologies.

scholarly journals The influence of study characteristics on coordinate-based fMRI meta-analyses

2017 ◽  
Author(s):  
Han Bossier ◽  
Ruth Seurinck ◽  
Simone Kühn ◽  
Tobias Banaschewski ◽  
Gareth J. Barker ◽  
...  
Keyword(s):  
Random Effects ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Group Analysis ◽  
Likelihood Estimation ◽  
Ordinary Least Squares ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Activation Likelihood Estimation ◽  
Meta Analyses

AbstractGiven the increasing amount of neuroimaging studies, there is a growing need to summarize published results. Coordinate-based meta-analyses use the locations of statistically significant local maxima with possibly the associated effect sizes to aggregate studies. In this paper, we investigate the influence of key characteristics of a coordinate-based meta-analysis on (1) the balance between false and true positives and (2) the reliability of the outcome from a coordinate-based meta-analysis. More particularly, we consider the influence of the chosen group level model at the study level (fixed effects, ordinary least squares or mixed effects models), the type of coordinate-based meta-analysis (Activation Likelihood Estimation, fixed effects and random effects meta-analysis) and the amount of studies included in the analysis (10, 20 or 35). To do this, we apply a resampling scheme on a large dataset (N = 1400) to create a test condition and compare this with an independent evaluation condition. The test condition corresponds to subsampling participants into studies and combine these using meta-analyses. The evaluation condition corresponds to a high-powered group analysis. We observe the best performance when using mixed effects models in individual studies combined with a random effects meta-analysis. This effect increases with the number of studies included in the meta-analysis. We also show that the popular Activation Likelihood Estimation procedure is a valid alternative, though the results depend on the chosen threshold for significance. Furthermore, this method requires at least 20 to 35 studies. Finally, we discuss the differences, interpretations and limitations of our results.

Effect of Application of Probiotics Based on Mixed Effects Models

2013 ◽  
Vol 631-632 ◽  
pp. 545-549
Author(s):  
Ya Ling Xu ◽  
Wei Wei Sui ◽  
Jun Jian Qiao
Keyword(s):  
Fixed Effects ◽  
Mixed Effects ◽  
Hebei Province ◽  
Mixed Effects Models ◽  
Linear Mixed Effects Model ◽  
Linear Mixed Effects ◽  
Independent Variables ◽  
Spss Software ◽  
Shed Light

In order to explore the effect of application of J-4 micro ecological preparation, based on the data from the experiment in the farm of Yixian County, Hebei Province, the research group established a linear mixed effects model , with time as independent variables, age and different formulations as the fixed effects, using spss software for analysis and solving, the results indicate that the model has the extremely good fitting and forecasting effect and method1 is the optimal ratio. The results will shed light on the further study of the role of probiotics .

An imputation approach for fitting two-part mixed effects models for longitudinal semi-continuous data

2020 ◽  
Vol 29 (11) ◽  
pp. 3351-3361
Author(s):  
Hyoyoung Choo-Wosoba ◽  
Debamita Kundu ◽  
Paul S Albert
Keyword(s):  
Random Effects ◽  
Fixed Effects ◽  
Clinical Trial Data ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Unbiased Estimation ◽  
Continuous Components ◽  
Wide Range ◽  
Parameter Values ◽  
Imputation Approach

Two-part mixed effects models are often used for analyzing longitudinal data with many zeros. Typically, these models are formulated with binary and continuous components separately with random effects that are correlated between the two components. Researchers have developed maximum-likelihood and Bayesian approaches for fitting these models that often require using particular software packages or very specialized software. We propose an imputation approach that will allow practitioners to separately use standard linear and generalized linear mixed models to estimate the fixed effects for two-part mixed effects models with complex random effects structures. An approximation to the conditional distribution of positive measurements given an individual’s pattern of non-zero measurements is proposed that can be easily estimated and then imputed from. We show that for a wide range of parameter values, the imputation approach results in nearly unbiased estimation and can be implemented with standard software. We illustrate the proposed imputation approach for the analysis of longitudinal clinical trial data with many zeros.

Sign in / Sign up

Export Citation Format

Share Document