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.

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

2021 ◽  
Author(s):  
Н.Н. Дубенок ◽  
В.В. Кузьмичев ◽  
А.В. Лебедев
Keyword(s):  
Fixed Effects ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Fixed Effects Model ◽  
Permanent Sample Plots ◽  
Diameter At Breast Height ◽  
Breast Height ◽  
Russian State ◽  
Pine Stands ◽  
The Relationship

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.

A note on Griffing's models for the diallel cross

1975 ◽  
Vol 85 (3) ◽  
pp. 575-576 ◽  
Author(s):  
B. K. Thompson
Keyword(s):  
Fixed Effects ◽  
Diallel Cross ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Fixed Effects Model

SUMMARYSome misconceptions concerning the application of Griffing's fixed effects model I and mixed effects model B are discussed.

Repeated Measurement Designs

1983 ◽  
Vol 32 (3-4) ◽  
pp. 153-168 ◽  
Author(s):  
A, C. Mukhopadhyay ◽  
Rita Saha
Keyword(s):  
Fixed Effects ◽  
Mixed Effects ◽  
Repeated Measurement ◽  
Mixed Effects Model ◽  
Fixed Effects Model

In the present paper Repeated Measurement Designs (RMD's) have been studied under mixed effects model, assuming unit effects to be random and most of the optimality results of RMD's proved under fixed effects model by Hedayat et. al (1978), Magda (1980) and Cheng et. al (1980) have been reestablished in the context of mixed effects model.

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.

The relationship between migraine and infant colic: A systematic review and meta-analysis

Cephalalgia ◽  
2014 ◽  
Vol 35 (1) ◽  
pp. 63-72 ◽  
Author(s):  
Amy A Gelfand ◽  
Peter J Goadsby ◽  
I Elaine Allen
Keyword(s):  
Systematic Review ◽  
Random Effects ◽  
Odds Ratio ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Random Effects Model ◽  
Fixed Effects Model ◽  
Primary Analysis ◽  
Infant Colic ◽  
The Relationship

Context Infant colic is a common and distressing disorder of early infancy. Its etiology is unknown, making treatment challenging. Several articles have suggested a link to migraine. Objective The objective of this article was to perform a systematic review and, if appropriate, a meta-analysis of the studies on the relationship between infant colic and migraine. Data sources Studies were identified by searching PubMed and ScienceDirect and by hand-searching references and conference proceedings. Study selection For the primary analysis, studies specifically designed to measure the association between colic and migraine were included. For the secondary analysis, studies that collected data on colic and migraine but were designed for another primary research question were also included. Data extraction Data were abstracted from the original studies, through communication with study authors, or both. Two authors independently abstracted data. Main outcomes and measures The main outcome measure was the association between infant colic and migraine using both a fixed-effects model and a more conservative random-effects model. Results Three studies were included in the primary analysis; the odds ratio for the association between migraine and infant colic was 6.5 (4.6–8.9, p < 0.001) for the fixed-effects model and 5.6 (3.3–9.5, p = 0.004) for the random-effects model. In a sensitivity analysis wherein the study with the largest effect size was removed, the odds ratio was 3.6 (95% CI 1.7–7.6, p = 0.001) for both the fixed-effects model and random-effects model. Conclusions In this meta-analysis, infant colic was associated with increased odds of migraine. If infant colic is a migrainous disorder, this would have important implications for treatment. The main limitation of this meta-analysis was the relatively small number of studies included.

A big data approach to examining social bots on Twitter

2019 ◽  
Vol 33 (4) ◽  
pp. 369-379 ◽  
Author(s):  
Xia Liu
Keyword(s):  
Big Data ◽  
Fixed Effects ◽  
Latent Dirichlet Allocation ◽  
User Generated Content ◽  
Fixed Effects Model ◽  
Data Set ◽  
Information Distortion ◽  
Content Type ◽  
Related Information ◽  
Brand Reputation

Purpose Social bots are prevalent on social media. Malicious bots can severely distort the true voices of customers. This paper aims to examine social bots in the context of big data of user-generated content. In particular, the author investigates the scope of information distortion for 24 brands across seven industries. Furthermore, the author studies the mechanisms that make social bots viral. Last, approaches to detecting and preventing malicious bots are recommended. Design/methodology/approach A Twitter data set of 29 million tweets was collected. Latent Dirichlet allocation and word cloud were used to visualize unstructured big data of textual content. Sentiment analysis was used to automatically classify 29 million tweets. A fixed-effects model was run on the final panel data. Findings The findings demonstrate that social bots significantly distort brand-related information across all industries and among all brands under study. Moreover, Twitter social bots are significantly more effective at spreading word of mouth. In addition, social bots use volumes and emotions as major effective mechanisms to influence and manipulate the spread of information about brands. Finally, the bot detection approaches are effective at identifying bots. Research limitations/implications As brand companies use social networks to monitor brand reputation and engage customers, it is critical for them to distinguish true consumer opinions from fake ones which are artificially created by social bots. Originality/value This is the first big data examination of social bots in the context of brand-related user-generated content.

Assessing the Effect of Mansionization on Suburban Single-Family House Sales Prices

2019 ◽  
pp. 0739456X1983315
Author(s):  
Suzanne Lanyi Charles
Keyword(s):  
Random Effects ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Single Family ◽  
Socioeconomic Characteristics ◽  
House Values ◽  
Crossed Random Effects ◽  
Family House

Using observed single-family house sales in the inner-ring suburbs of Chicago from 2010 through 2017, this paper uses a multilevel mixed-effects model with crossed random effects to estimate the effect that millennium mansions—new, large single-family houses—have on the sales prices of nearby single-family houses. Controlling for property, sale timing, and surrounding neighborhood socioeconomic characteristics, the study finds that mansionization is associated with an increase in the sales prices of neighboring houses. Long-term residents of a neighborhood undergoing mansionization should not fear a decrease in their house values; however, decreases in neighborhood affordability may result in exclusionary displacement.

scholarly journals The Negative Effect of Smartphone Use on Academic Performance May Be Overestimated: Evidence From a 2-Year Panel Study

2020 ◽  
Vol 31 (11) ◽  
pp. 1351-1362
Author(s):  
Andreas Bjerre-Nielsen ◽  
Asger Andersen ◽  
Kelton Minor ◽  
David Dreyer Lassen
Keyword(s):  
Academic Performance ◽  
Fixed Effects ◽  
Panel Study ◽  
Student Characteristics ◽  
Fixed Effects Model ◽  
Data Set ◽  
Course Characteristics ◽  
Negative Effect ◽  
Smartphone Use ◽  
The Relationship

In this study, we monitored 470 university students’ smartphone usage continuously over 2 years to assess the relationship between in-class smartphone use and academic performance. We used a novel data set in which smartphone use and grades were recorded across multiple courses, allowing us to examine this relationship at the student level and the student-in-course level. In accordance with the existing literature, our results showed that students’ in-class smartphone use was negatively associated with their grades, even when we controlled for a broad range of observed student characteristics. However, the magnitude of the association decreased substantially in a fixed-effects model, which leveraged the panel structure of the data to control for all stable student and course characteristics, including those not observed by researchers. This suggests that the size of the effect of smartphone usage on academic performance has been overestimated in studies that controlled for only observed student characteristics.

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