General Linear Test Research Articles

Total Carbon Storage in Uneven-Aged Pure Beech Stands in the Western Part of the Balkans

Forest ecosystems represent one of the largest and most important ecosystems on Earth, containing close to 80% of the biomass of our planet. As such, they play a significant role in the global carbon cycle because through photosynthesis, forests absorb more carbon than they emit and thus accumulate it. The most important species in deciduous forests in Europe, European beech (Fagus sylvatica L.), is of exceptional importance from the aspect of carbon storage. Considering that the state of carbon in pure beech forests is poorly investigated in the western part of the Balkans, the need for total carbon research was imposed to complete the picture of its stocks and factors that impact it. Research on total carbon (TC) storage in uneven-aged pure beech stands in the western part of the Balkans was carried out in three regions located approximately at the same latitude, but different longitude, imposing different macro-habitat characteristics. This research aimed to determine the TC stock and to examine the effects of orographic factors, stand canopy, and macroclimate on its values. TC stock in forest biomass was determined using appropriate regression equations and formulas, while soil organic carbon stock was determined using ICP forests methodology. Effects of different factors on carbon stock were examined using ANOVA (Type II Sums of Squares), General Linear Hypothesis Test (GLHT), and regression analyses. It was found that the largest TC stock is located in the region of Eastern Serbia (SRB) where its macroclimate is classified as suitable for hornbeam and sessile oak or mixed beech-oak stands. It was found that anthropogenic activity plays a significant role in the size of the carbon stock stored in above-ground biomass via alteration of forest canopy. The results also indicate that Aboveground Carbon (AGC) stocks are approximately proportional to Belowground Carbon (BGC; C in belowground biomass + soil C) stocks. What makes the difference is the structure of BGC, as the share of Soil Organic Carbon (SOC) is higher in the regions of Eastern Republic of Srpska (ERS) and Western Republic of Srpska (WRS), which are climatically classified as highly suitable for beech. Further analysis has shown that the amount of SOC decreases with increasing aridity levels. Given the results, management goals should be aimed at increasing the stock of biomass for the sake of carbon sequestration and for reducing the adverse effects of climate change, as a large amount of carbon can be stored in the above-ground and belowground biomass.

Empirical likelihood M‐estimation for the varying‐coefficient model with functional response

AbstractThis work is motivated by a gap in the functional data analysis literature, particularly in the context of neuroimaging, regarding the ability of functional models to robustly accommodate intra‐observation dependence. In response, we propose an M‐estimator based on generalized empirical likelihood for the varying‐coefficient model with a functional response. We develop statistical inference procedures, simultaneous confidence regions, and a global general linear hypothesis test for the model's functional coefficient. Our theoretical results establish the weak convergence of the log‐likelihood ratio process, a nonparametric version of Wilks' theorem for the log‐likelihood ratio, and asymptotic properties of the proposed estimator. Through a simulation study, we show that the proposed confidence sets have close‐to‐nominal coverage probabilities. In a real‐world application to a neuroimaging dataset, we show that mini‐mental state examination score and apolipoprotein E genotype have significant associations with fractional anisotropy, while associations with gender and age are only present at high quantile levels.

Factors that determine the connectedness with nature in rural and urban contexts.

Connectedness with nature is considered a key element for the future of conservation. There are both internal and external factors that determine the levels of connectedness with nature. Among these factors are gender, age, knowledge about the environment and place of residence. In the latter case, there may be differences in how urban and rural dwellers perceive nature, based on their experiences and contact with it. The main objective of this research is to evaluate and establish the factors that influence and determine the levels of connection with nature, examining how these factors relate and interact with each other, taking the urban and rural context as starting point. The ABC-CNS scale, which addresses the affective, behavioural and cognitive aspects of the connection with nature, was applied via online questionnaire to a sample of university students from two countries, Spain (496 students) and Ecuador (872 students), who were also clustered according to career, age, gender, and place of residence. The results obtained through four General Linear Mixed Models (ABC-CNS and its dimensions as response variables) and LSD test, demonstrated that the ABC-CNS scale presented significant differences for all the variables analyzed (place of residence, gender, age, and career), also demonstrating which levels influence and interact in higher ABC-CNS values. Finally, the study concludes that the analyzed factors contribute to the development of the connection with nature. In the case of place of residence, attention should be given to the specific settings of the environments under study.

Robust Inference on Infinite and Growing Dimensional Time‐Series Regression

We develop a class of tests for time‐series models such as multiple regression with growing dimension, infinite‐order autoregression, and nonparametric sieve regression. Examples include the Chow test and general linear restriction tests of growing rank p. Employing such increasing p asymptotics, we introduce a new scale correction to conventional test statistics, which accounts for a high‐order long‐run variance (HLV), which emerges as p grows with sample size. We also propose a bias correction via a null‐imposed bootstrap to alleviate finite‐sample bias without sacrificing power unduly. A simulation study shows the importance of robustifying testing procedures against the HLV even when p is moderate. The tests are illustrated with an application to the oil regressions in Hamilton (2003).

Comparative fertility behavior in two ethnic groups of Fars and Turkmen in North Khorasan

Background and purpose: Cohesion and sense of ethnicity on the one hand and religious differences on the other hand can be effective in shaping reproductive behaviors. The aim of this study was to compare the reproductive behavior of Fars and Turkmen in North Khorasan. Materials and Methods: This cross-sectional study was performed on 406 Persian and Turkmen women using a researcher-made fertility behavior questionnaire. Data were analyzed using SPSS21 software and descriptive and analytical indicators. Results: Reproductive behaviors between the two groups in terms of number of children (0.001). The best time of birth of the first child (0.043), the interval between the first and second pregnancy (0.002), the tendency to have children again (0.002), the number of desired children (0.025) and the current method of contraception There was a significant difference but the decision to continue or terminate an unwanted pregnancy (0.074) was not significantly different. General linear test showed that with the introduction of demographic variables to measure the effect of the number of children in the analysis, the effect of ethnicity on the number of children was removed, but the variables of mother age (0.001), age of spouse (0.001), education of wife and spouse (0.001) and female occupation (0.001) remained as effective variables on the number of children. Conclusion: Today, childbearing has changed more than other family values, therefore, in order to achieve appropriate population policies, population policy should be based on economic, social, cultural and demographic realities of society.

Ongoing Improvement in Acute Ischemic Stroke Therapy Per Concurrent Guidelines and Easily Implementable Quality Improvement Protocol

Background: Despite proven efficacy of intravenous tissue plasminogen activator (tPA) and endovascular thrombectomy (EVT) in acute ischemic stroke, there has been slow administration of these therapies in the real world practice. We examined the ongoing quality improvement in acute stroke care at our comprehensive stroke center. Methods: Consecutive patients with acute ischemic stroke from 2013 to 2018 were studied. Patients were managed using Code Stroke algorithm per concurrent AHA guidelines and a simple quality improvement protocol implemented in 2015. Demographics and clinical data were collected from Get-With-The-Guideline-Stroke registry and electronic medical records. Patients were divided into 3 groups per admission and implementation date of quality improvement initiatives. Quality measures, including rates of intravenous tPA and EVT, door-to-needle (DTN) time, and door-to-puncture (DTP) time, were analyzed with general mean linear regression models and Jonckheere-Terpstra test. Results: Of the 1,369 eligible patients presenting within 24 hours of symptom onset or wakeup stroke, the rate of intravenous tPA was 20%, 30% and 22%, respectively, in 2013-2014, 2015-2016, and 2017-2018. In contrast, EVT rate was 9%, 14% and 15%, respectively. Based on Jonckheere-Terpstra test, there was significant ongoing improvement in the median DTN time (57, 45, 39 minutes; p < 0.001) and DTP time (172, 130, 114 minutes; p =0.009) during the 3 time periods, with DTN time ≤ 60 and ≤45 minutes in 80% and 63% patients, respectively, in 2017-2018. Conclusions: Getting with the guidelines and simple quality improvement initiatives are associated with satisfactory rates of acute stroke therapy and ongoing improvement in door to treatment times.

High-dimensional general linear hypothesis tests via non-linear spectral shrinkage

We are interested in testing general linear hypotheses in a high-dimensional multivariate linear regression model. The framework includes many well-studied problems such as two-sample tests for equality of population means, MANOVA and others as special cases. A family of rotation-invariant tests is proposed that involves a flexible spectral shrinkage scheme applied to the sample error covariance matrix. The asymptotic normality of the test statistic under the null hypothesis is derived in the setting where dimensionality is comparable to sample sizes, assuming the existence of certain moments for the observations. The asymptotic power of the proposed test is studied under various local alternatives. The power characteristics are then utilized to propose a data-driven selection of the spectral shrinkage function. As an illustration of the general theory, we construct a family of tests involving ridge-type regularization and suggest possible extensions to more complex regularizers. A simulation study is carried out to examine the numerical performance of the proposed tests.

Power Analysis and Sample Size Planning in ANCOVA Designs

The analysis of covariance (ANCOVA) has notably proven to be an effective tool in a broad range of scientific applications. Despite the well-documented literature about its principal uses and statistical properties, the corresponding power analysis for the general linear hypothesis tests of treatment differences remains a less discussed issue. The frequently recommended procedure is a direct application of the ANOVA formula in combination with a reduced degrees of freedom and a correlation-adjusted variance. This article aims to explicate the conceptual problems and practical limitations of the common method. An exact approach is proposed for power and sample size calculations in ANCOVA with random assignment and multinormal covariates. Both theoretical examination and numerical simulation are presented to justify the advantages of the suggested technique over the current formula. The improved solution is illustrated with an example regarding the comparative effectiveness of interventions. In order to facilitate the application of the described power and sample size calculations, accompanying computer programs are also presented.

Multiparametric Quantitative Brain MRI in Neurological and Hepatic Forms of Wilson's Disease.

In Wilson's disease (WD), demyelination, rarefaction, gliosis, and iron accumulation in the deep gray matter cause opposing effects on T2 -weighted MR signal. However, the degree and interplay of these changes in chronically treated WD patients has not been quantitatively studied. To compare differences in brain multiparametric mapping between controls and chronically treated WD patients with neurological (neuro-WD) and hepatic (hep-WD) forms to infer the nature of residual WD neuropathology. Cross-sectional. Thirty-eight WD patients (28 neuro-WD, 10 hep-WD); 26 healthy controls. 3.0T: susceptibility, T2 *, T2 , T1 relaxometry; 1.5T: T2 , T1 relaxometry. The following 3D regions of interest (ROIs) were manually segmented: globus pallidus, putamen, caudate nucleus, and thalamus. Mean bulk magnetic susceptibility, T2 *, T2 , and T1 relaxation times were calculated for each ROI. The effect of group (neuro-WD, hep-WD, controls) and age was assessed using a generalized least squares model with different variance for each ROI and quantitative parameter. A general linear hypothesis test with Tukey adjustment was used for post-hoc between-group analysis; P < 0.05 was considered significant. Susceptibility values were higher in all ROIs in neuro-WD compared to controls and hep-WD (P < 0.001). In basal ganglia, lower T2 and T2 * were found in neuro-WD compared to controls (P < 0.01) and hep-WD (P < 0.05) at 3.0T. Much smaller intergroup differences for T2 in basal ganglia were observed at 1.5T compared to 3.0T. In the thalamus, increased susceptibility in neuro-WD was accompanied by increased T1 at both field strengths (P < 0.001 to both groups), and an increased T2 at 1.5T only (P < 0.001 to both groups). We observed significant residual brain MRI abnormalities in neuro-WD but not in hep-WD patients on chronic anticopper treatment. Patterns of changes were suggestive of iron accumulation in the basal ganglia and demyelination in the thalamus; 3.0T was more sensitive for detection of the former and 1.5T of the latter abnormality. 2 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2020;51:1829-1835.

Frequent Cognitive Impairment in Patients With Disorders Along the Heart-Brain Axis.

Background and Purpose- Patients with cardiovascular disease are at increased risk for cognitive decline. We studied the occurrence and profile of cognitive impairment in 3 patient groups as exemplar conditions of hemodynamic disturbances at different levels of the heart-brain axis, including patients with heart failure (HF), carotid occlusive disease (COD), and patients with cognitive complaints and vascular brain injury on magnetic resonance imaging (possible vascular cognitive impairment [VCI]). Methods- In 555 participants (160 HF, 107 COD, 160 possible VCI, 128 reference participants; 68±9 years; 36% F; Mini-Mental State Examination 28±2), we assessed cognitive functioning with a comprehensive test battery. Test scores were transformed into z-scores. Compound z-scores were constructed for: memory, language, attention/psychomotor speed, executive functioning, and global cognitive functioning. We rated cognitive domains as impaired when z-score≤-1.5. Based on the number of impaired domains, patients were classified as cognitively normal, minor, or major cognitive impairment. We used general linear models and χ2 tests to compare cognitive functioning between patient groups and the reference group. Results- Age, sex, and education adjusted global cognitive functioning z-score was lower in patients with COD (β [SE]=-0.46 [0.10], P<0.001) and possible VCI (β [SE]=-0.80 [0.09], P<0.001) compared with reference participants. On all domains, z-scores were lower in patients with COD and possible VCI compared with reference participants. Patients with HF had lower z-scores on attention/speed and language compared with reference participants. Cognitive impairment was observed in 18% of HF, 36% of COD, and 45% possible VCI. There was no difference in profile of impaired cognitive domains between patient groups. Memory and attention-psychomotor speed were most commonly affected, followed by executive functioning and language. Conclusions- A substantial part of patients with HF and COD had cognitive impairment, which warrants vigilance for the occurrence of cognitive impairment. These results underline the importance of an integrative approach in medicine in patients presenting with disorders in the heart-brain axis.

Leukocyte telomere length, lipid parameters and gestational diabetes risk: a case-control study in a Chinese population

Telomere length (TL) is linked to various age-related diseases, but little is known about telomeres in gestational diabetes mellitus (GDM). We surveyed 509 subjects (113 GDM patients and 396 frequency matched controls) in Nanjing Drum Tower Hospital, Jiangsu province of eastern China. Relative telomere length (RTL) of genomic DNA extracted from peripheral blood leukocytes was measured using quantitative polymerase chain reaction (qPCR). Odds ratios (OR) and 95% confidence interval (CI) of GDM risk were calculated across tertiles of RTL using logistic regression model. Lipid parameters during the third trimesters of gestation (after 32 weeks) were collected from medical records. The general linear correlation test was used to explore the associations of lipid parameters with RTL. Our results showed that the RTL in GDM patients were significantly shorter than controls (0.302 ± 0.112 vs. 0.336 ± 0.164, P = 0.046). However, the GDM risk was significantly increased in subjects with median RTL (adjusted OR [aOR]: 1.936, 95% CI: 1.086, 3.453, P = 0.025) and the shortest RTL (aOR: 1.795, 95% CI: 1.004, 3.207, P = 0.048), compared to subjects with longest RTL. We also demonstrated that the lipid ratios (TC/TG, LDL/TG, HDL/TG, LDL/TC, TC/LDL) were significantly associated with RTL among controls. Overall, the present study indicated that attrition of telomeres would increase GDM risk among pregnant women, and the altered lipid levels may play an important role in RTL related GDM risk and pathogenesis.

Superconvergent IMEX peer methods

In this paper we will focus on numerical methods for differential equations with both stiff and nonstiff parts. This kind of problems can be treated efficiently by implicit-explicit (IMEX) methods and here we investigate a class of s-stage IMEX peer methods of order p=s for variable and p=s+1 for constant step sizes. They are combinations of s-stage superconvergent implicit and explicit peer methods. We construct methods of order p=s+1 for s=3,4,5 where we compute the free parameters numerically to give good stability with respect to a general linear test problem frequently used in the literature. Numerical comparisons with two-step IMEX Runge–Kutta methods confirm the high potential of the new constructed superconvergent IMEX peer methods.

Task difficulty prediction of figural analogies

The purpose of this psychometric study is to explain performance on cognitive tasks pertaining Analogical Reasoning that were taken into consideration during the construction of a Test of Figural Analogies. For this purpose, a general Linear Logistic Test Model (LLTM) was mainly used for data analysis. A 30-itemed Test of Figural Analogies was administered to a sample of 422 students from Argentina, and eight of these items were administered along with a Matrices Test to 84 participants mostly from Germany. Women represented 77% and 76% of each respective sample. Indicators of validity and reliability show acceptable results. Item difficulties can be predicted by a set of nine Cognitive Operations to a satisfactory extent, as the Pearson correlation between the Rasch model and the LLTM item difficulty parameters r=.89, the mean prediction error is slightly different between the two models, and there is an overall effect of the number of combined rules on item difficulty (F(3,23)=15.16, p<.001) with an effect size η2=.66 (large effect). Results suggest that almost all rotation rules are highly influential on item difficulty.

Genetic Variants and Systemic Complement Activation Levels Are Associated With Serum Lipoprotein Levels in Age-Related Macular Degeneration.

Genetic variants in genes encoding components of lipid metabolism have been associated with AMD. The aims of this study were to evaluate the relation of these genetic variants with serum lipid levels in AMD in a large case-control cohort (n = 3070) and to test for correlations between lipids and complement activation. Single nucleotide polymorphisms (SNPs) in eight lipid metabolism genes, previously described to be associated with AMD, were genotyped and tested for their association in our case-control cohort. Serum apolipoprotein B (ApoB), apolipoprotein AI (Apo-AI), cholesterol, triglycerides (TG), high-density lipoprotein-cholesterol (HDLC), and complement activation levels (C3d/C3) were measured and tested for association with AMD. Non-HDL cholesterol and LDL were inferred based on the measurements of the other lipids and lipoproteins. General linear models and χ2 tests were used to evaluate the relation of SNPs and lipids/lipoproteins to the disease as well as their interrelations. Significant genotypic associations with AMD were observed for SNPs in CETP, APOE, and FADS1. The serum levels of Apo-AI and HDLC were significantly higher in patients compared with controls. Triglycerides (TG) levels were lower in AMD compared with controls. A cumulative effect was observed for APOE and CETP genotypes on HDLC and Apo-AI levels. Complement activation levels correlated positively with HDLC and Apo-AI, and negatively with TG. Both the lipids/lipoproteins and the complement activation levels associate independently to AMD. This study bridges the gap between genetic associations and physiological lipid levels in AMD. Additionally, the observed correlations between complement activation and lipid levels link two major systems that previously were always assessed independently.

안면골격 유형에 따른 하악 전치 치조골의 형태 차이: Cone-beam CT를 이용한 정량적 평가

Purpose: The aim of this study was to investigate differences between the morphology of the mandibular symphysis and four facial skeletal types. Materials and Methods: 40 cone-beam computed tomographies were selected and classified in to 4 groups according to their vertical and anterior-posterior skeletal patterns. The bone volume (mm³) of the symphysis, the cross sectional area corresponding to the 4 mandibular incisors’ axis: the cross sectional area of total bone (mm²), the area of the cancellous bone (mm²) and the thickness (mm) of labial and lingual alveolar bone at 2 mm, 3 mm under the cemento-enamel junction (CEJ) were measured. General linear model (GLM), Kruskal-Wallis test and Tukey honestly significant difference (HSD) test were subsequently used for statistical analysis. Results: The lingual cortical bone thickness of the lateral incisors at 2, 3 mm under CEJ was greater in the Class I low angle group than the other 3 groups (P < 0.05). There were no statistically significant differences in the volume of the mandibular incisor bony support, cross-sectional area of total bone and cancellous bone at the mandibular incisor’ axis. Conclusion: Patients in Class I, low angle group have a thicker lingual mandibular symphysis than Class I, high angle patients.

The General Linear Test in the Ridge Regression

We derive a test statistic for the general linear test in the ridge regression model. The exact distribution for the test statistic is too difficult to derive; therefore, we suggest an approximate reference distribution. We use numerical studies to verify that the suggested distribution for the test statistic is appropriate. A asymptotic result for the test statistic also is considered.

Performance effects of stakeholder interaction in emerging economies: evidence from Brazil

Firm survival in emerging economies is often related to having access to valuable resources that are in stakeholders' hands. However, the literature on strategy in emerging economies provides scant information on the efficiency of acquiring stakeholder resources and its effect on firm performance. We investigated the stakeholder interaction effects on performance of domestic firms competing in an emerging market (Wright, Filatotchev, Hoskisson, & Peng, 2005) from a contractual perspective (Williamson, 1985). We argue that interacting stakeholders in a contractual set yield synergistic governance structures that allow firms more efficient access to external resources. Using a sample of 267 firms in Brazil (secondary data), we explored different patterns in stakeholder contracting with community, government, top management, and employees. A three-stage analysis process was devised: cluster analysis, general linear model estimation and verification tests. Results suggest that stakeholder interaction has a positive impact on firm performance. The conjoint effect of government and community contracts was found to yield superior firm performance as they provide a basic structure for contracting with other interacting stakeholders.

Statistical models for traffic noise at signalized intersections

A total of 14,235 noise levels measurements were utilized in developing statistical models that have the capability to predict different noise levels including: equivalent, maximum, or minimum noise level in terms of parameters affecting each level. Different parameters expected to have an effect on noise levels were collected. These parameters included traffic volume, composition of traffic, traffic speed, horn using effect, number of lanes, width of lanes, approach width, road slope, and pavement surface texture. The parameters affecting each noise level were selected based on simple correlation matrices, scatter plots, and statistical t -test. Different forms of models were evaluated for each noise level. The best model describing the relationship between each noise level and parameters affecting it are presented in this paper. The reliability of the nonlinear developed models were judged based on coefficient of multiple determination ( R 2 ), the significance of each variable at α -level of 0.05, and the standard error of the estimates. While the reliability of linear developed models were judged based on the general linear regression tests represented by F -value and t -value in addition to the coefficient of multiple determination ( R 2 ), the significance of each variable at α -level of 0.05, and the standard error of the estimates. Based on the analysis of the collected data, three groups of models were developed. The first group of models predicts the equivalent noise level in terms of traffic volume, traffic speed, distance, heavy vehicles and British Pendulum Number (BPN). The second group presents models that describe the relationships between maximum noise levels, heavy vehicles and use of horn. While, the third group presents minimum noise level prediction models in terms of BPN and lane width. A verification of the developed models was performed by comparing the predictive noise levels with those measured at different sites. Results of this verification indicated that the developed models were found to have good prediction capability.

Pooled analysis of data from multiple quantitative trait locus mapping populations

Quantitative trait locus (QTL) analysis on pooled data from multiple populations (pooled analysis) provides a means for evaluating, as a whole, evidence for existence of a QTL from different studies and examining differences in gene effect of a QTL among different populations. Objectives of this study were to: (1) develop a method for pooled analysis and (2) conduct pooled analysis on data from two soybean mapping populations. Least square interval mapping was extended for pooled analysis by inclusion of populations and cofactor markers as indicator variables and covariate variables separately in the multiple linear models. The general linear test approach was applied for detecting a QTL. Single population-based and pooled analyses were conducted on data from two F(2:3) mapping populations, Hamilton (susceptible) x PI 90763 (resistant) and Magellan (susceptible) x PI 404198A (resistant), for resistance to soybean cyst nematode (SCN) in soybean. It was demonstrated that where a QTL was shared among populations, pooled analysis showed increased LOD values on the QTL candidate region over single population analyses. Where a QTL was not shared among populations, however, the pooled analysis showed decreased LOD values on the QTL candidate region over single population analyses. Pooled analysis on data from genetically similar populations may have higher power of QTL detection than single population-based analyses. QTLs were identified by pooled analysis on linkage groups (LGs) G, B1 and J for resistance to SCN race 2 whereas QTLs on LGs G, B1 and E for resistance to SCN race 5 in soybean PI 90763 and PI 404198A. QTLs on LG G and B1 were identified in both PI 90763 and PI 404198A whereas QTLs on LG E and J were identified in PI 90763 only. QTLs on LGs G and B1 for resistance to race 2 may be the same or closely linked with QTLs on LG G and B1 for resistance to race 5, respectively. It was further demonstrated that QTLs on G and B1 carried by PI 90763 were not significantly different in gene effect from QTLs on LGs G and B1 in PI 404198A, respectively.

A Note on Sample Size Determination for a Nonparametric Test of Location

Sample size determination methods are considered for hypothesis testing about location parameters of two continuous distributions using independent random samples and the Mann–Whitney–Wilcoxon (MWW) test, for a specified shift, size, and power. These methods are based on the so-called “Noether's formula,” derived from a normal approximation to the power of the MWW test, and a pilot sample from each of the distributions. Compared with alternate methods, including the one using bootstrap similar to that of Hamilton and Collings (1991) the new methods are shown to be at least as good in terms of accuracy and substantially more efficient in terms of speed and variability. The simpler method, using linearly smoothed empirical cdf's of the pilot samples and requiring no bootstrapping, is recommended for practical use. Extensions and adaptations for obtaining an upper confidence bound on the sample size and to general linear rank tests are indicated.