Testing the differences of LT50, LD50, or ED50

2018 ◽  
Vol 48 (6) ◽  
pp. 729-734 ◽  
Author(s):  
Juha Lappi ◽  
Jaana Luoranen
Keyword(s):  
Approximate Method ◽  
Generalized Linear Models ◽  
Mixed Models ◽  
Logistic Model ◽  
Linear Models ◽  
Generalized Linear Mixed Models ◽  
Wald Test ◽  
Delta Method ◽  
Treatment Variable ◽  
The Relationship

An approximate method is derived for testing the differences of LT50, LD50, or ED50, which indicate the temperature or dose needed to kill or damage half of the plants, respectively. It is assumed that a logistic model is used to describe the relationship between probability and a treatment variable in the framework of generalized linear mixed models or generalized linear models. The method is based on the delta method and the Wald test. In the forest sciences, this method can be used when dose, temperature, or time responses are compared in different treatments, cultivars, or origins.

PERFORMANCE OF MIXED EFFECTS FOR CLUSTERED COUNTING DATA MODELS

2020 ◽  
Vol 3 (2) ◽  
pp. 34-41
Author(s):  
Intesar N. El-Saeiti ◽  
Khalil Mostafa ALsawi
Keyword(s):  
Generalized Linear Models ◽  
Standard Error ◽  
Mixed Models ◽  
Linear Models ◽  
Generalized Linear Mixed Models ◽  
Linear Mixed Models ◽  
Likelihood Estimation ◽  
Real Data ◽  
Estimation Technique ◽  
Counting Data

This article is concerned with hierarchical generalized linear models. It includes generalized linear models and generalized linear mixed models, which are related to linear models. In generalized linear mixed models, the dependent variable and the standard error follow any distribution from the exponential family, e.g. normal, Poisson, binomial, gamma, etc. We studied counting data, and then use the Poisson-gamma model,where the dependentvariable follows the Poisson distribution and the standard error follow the gamma distribution. Several estimation techniques can be used for generalized linear mixed model. In this paperthe hierarchical likelihood estimation technique was used to prove the performance of H-likelihood methodwhen thecounting data were balanced or unbalanced. Real data were used to test the performance of Poisson-gamma H-likelihood estimation method in case of balanced and unbalanced counting data.When real data used in the past research for another problem, it was noticed that the performance of the hierarchical likelihood estimation technique gave a close approximations in the event of balanced and unbalanced counting data, and the output of the technique was approximately equivalent in both instances.

scholarly journals The Relationships Between Serum DHEA-S and AMH Levels in Infertile Women: A Retrospective Cross-Sectional Study

2021 ◽  
Vol 10 (6) ◽  
pp. 1211
Author(s):  
Li-Te Lin ◽  
Kuan-Hao Tsui
Keyword(s):  
Generalized Linear Models ◽  
Large Scale ◽  
Linear Models ◽  
Positive Association ◽  
Cross Sectional Study ◽  
Dehydroepiandrosterone Sulphate ◽  
Sectional Study ◽  
Cross Sectional ◽  
Infertile Women ◽  
The Relationship

The relationship between serum dehydroepiandrosterone sulphate (DHEA-S) and anti-Mullerian hormone (AMH) levels has not been fully established. Therefore, we performed a large-scale cross-sectional study to investigate the association between serum DHEA-S and AMH levels. The study included a total of 2155 infertile women aged 20 to 46 years who were divided into four quartile groups (Q1 to Q4) based on serum DHEA-S levels. We found that there was a weak positive association between serum DHEA-S and AMH levels in infertile women (r = 0.190, p < 0.001). After adjusting for potential confounders, serum DHEA-S levels positively correlated with serum AMH levels in infertile women (β = 0.103, p < 0.001). Infertile women in the highest DHEA-S quartile category (Q4) showed significantly higher serum AMH levels (p < 0.001) compared with women in the lowest DHEA-S quartile category (Q1). The serum AMH levels significantly increased across increasing DHEA-S quartile categories in infertile women (p = 0.014) using generalized linear models after adjustment for potential confounders. Our data show that serum DHEA-S levels are positively associated with serum AMH levels.

scholarly journals Relationship between Cycling Infrastructure and Transportation Cycling in a Small Urban Area

2021 ◽  
Vol 1 (1) ◽  
pp. 99-112
Author(s):  
Richard Larouche ◽  
Nimesh Patel ◽  
Jennifer L. Copeland
Keyword(s):  
Generalized Linear Models ◽  
Qualitative Data ◽  
Linear Models ◽  
The Other ◽  
Small City ◽  
The Road ◽  
The Past ◽  
Low Prevalence ◽  
The Relationship

The role of infrastructure in encouraging transportation cycling in smaller cities with a low prevalence of cycling remains unclear. To investigate the relationship between the presence of infrastructure and transportation cycling in a small city (Lethbridge, AB, Canada), we interviewed 246 adults along a recently-constructed bicycle boulevard and two comparison streets with no recent changes in cycling infrastructure. One comparison street had a separate multi-use path and the other had no cycling infrastructure. Questions addressed time spent cycling in the past week and 2 years prior and potential socio-demographic and psychosocial correlates of cycling, including safety concerns. Finally, we asked participants what could be done to make cycling safer and more attractive. We examined predictors of cycling using gender-stratified generalized linear models. Women interviewed along the street with a separate path reported cycling more than women on the other streets. A more favorable attitude towards cycling and greater habit strength were associated with more cycling in both men and women. Qualitative data revealed generally positive views about the bicycle boulevard, a need for education about sharing the road and for better cycling infrastructure in general. Our results suggest that, even in smaller cities, cycling infrastructure may encourage cycling, especially among women.

On estimating and testing associations between random coefficients from multivariate generalized linear mixed models of longitudinal outcomes

2015 ◽  
Vol 26 (3) ◽  
pp. 1130-1145 ◽  
Author(s):  
Susan K Mikulich-Gilbertson ◽  
Brandie D Wagner ◽  
Paula D Riggs ◽  
Gary O Zerbe
Keyword(s):  
Likelihood Ratio ◽  
Mixed Models ◽  
Generalized Linear Mixed Models ◽  
Mathematical Proof ◽  
Linear Mixed Models ◽  
Delta Method ◽  
Standard Errors ◽  
Ratio Test ◽  
Type I ◽  
Time Lags

Different types of outcomes (e.g. binary, count, continuous) can be simultaneously modeled with multivariate generalized linear mixed models by assuming: (1) same or different link functions, (2) same or different conditional distributions, and (3) conditional independence given random subject effects. Others have used this approach for determining simple associations between subject-specific parameters (e.g. correlations between slopes). We demonstrate how more complex associations (e.g. partial regression coefficients between slopes adjusting for intercepts, time lags of maximum correlation) can be estimated. Reparameterizing the model to directly estimate coefficients allows us to compare standard errors based on the inverse of the Hessian matrix with more usual standard errors approximated by the delta method; a mathematical proof demonstrates their equivalence when the gradient vector approaches zero. Reparameterization also allows us to evaluate significance of coefficients with likelihood ratio tests and to compare this approach with more usual Wald-type t-tests and Fisher’s z transformations. Simulations indicate that the delta method and inverse Hessian standard errors are nearly equivalent and consistently overestimate the true standard error. Only the likelihood ratio test based on the reparameterized model has an acceptable type I error rate and is therefore recommended for testing associations between stochastic parameters. Online supplementary materials include our medical data example, annotated code, and simulation details.

scholarly journals Examining the presence of nonlinear relationship between natural gas consumption and economic growth in nigeria

2017 ◽  
Vol 7 (4) ◽  
pp. 484-492
Author(s):  
Mukhtar Danladi Galadima ◽  
Abubakar Wambai Aminu
Keyword(s):  
Economic Growth ◽  
Natural Gas ◽  
Linear Models ◽  
Nonlinear Modeling ◽  
Wald Test ◽  
Nonlinear Relationship ◽  
Nonlinearity Test ◽  
Gas Consumption ◽  
Natural Gas Consumption ◽  
The Relationship

This paper examines the Presence of Nonlinear Relationship between Natural Gas Consumption and Economic Growth in Nigeria from 1981 to 2015. The Ramsey Reset test,Incremental F-test, and Wald test have been employed to test for non-linearity in the relationship between natural gas consumption and economic growth in Nigeria. The nonlinearity test results revealed that the relationship is nonlinear. However, the results are suggestive of the fact that linear models might not be the appropriate statistical tools for estimating the relationship between natural gas consumption and economic growth in Nigeria. Therefore, the paper recommends that the Nigeria’s policymakers consider taking into cognizance nonlinear modeling techniques as alternative tools for modeling, estimating and forecasting the relationship between natural gas consumption and economic growth in the country.

scholarly journals Relationship among atrial fibrillation, the CHA2DS2-VASc score and ischaemic stroke in patients with coronary artery disease: a propensity score matching study in Hebei, China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Boqun Shi ◽  
Demin Liu ◽  
Qian Wang ◽  
Xue Geng ◽  
Qian Hou ◽  
...  
Keyword(s):  
Ischaemic Stroke ◽  
Generalized Linear Models ◽  
Linear Models ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Stroke Patients ◽  
Cross Sectional ◽  
Stroke Group ◽  
Artery Disease ◽  
The Relationship

Abstract Background Recent evidence has shown that the pathogenesis of ischaemic stroke associated with atrial fibrillation (AF) is complex and involves other factors in addition to arrhythmias. The purpose of this study was to investigate the relationship among AF, CHA2DS2-VASc score and ischaemic stroke in patients with coronary artery disease (CAD) in Hebei, China. Methods A total of 2,335 patients with CAD from September 2016 to May 2019 at the Second Hospital of Hebei Medical University were included (mean age 62.73 ± 10.35 years, range 26–92 years; 41.58% female). This was a cross-sectional study, and participants were divided into non-stroke (n = 1997) and ischaemic stroke groups (n = 338). Propensity score matching (PSM) was performed to match ischaemic stroke patients with non-stroke patients in a 1:4 ratio. The relationship among AF, the CHA2DS2-VASc score and ischaemic stroke was evaluated using univariable generalized linear models for different sex, age, body mass index (BMI), CAD and CHA2DS2-VASc score subgroups. Univariable and multivariable generalized linear models were used to evaluate the relationship between AF and ischaemic stroke in the different models. Results Compared with that in the non-stroke group, the prevalence of AF (8.81% vs. 14.20%, P = 0.002) in the ischaemic stroke group was higher. The proportion of patients with ischaemic stroke was significantly different between the AF group and the non-AF group (28.74% vs. 19.04%, P = 0.003). An increasing CHA2DS2-VASc score was associated with a gradual increase in the prevalence of AF (P for trend < 0.001). Subgroup analysis showed that the trend towards increased stroke risk in the AF group was consistent across the various subgroups. The multivariable analysis demonstrated that AF was not associated with ischaemic stroke compared with the absence of AF (OR = 1.55, 95% CI 0.94–2.56, P = 0.087). Conclusion In our cross-sectional study, after adjustment for confounding factors, there was no association between AF and ischaemic stroke. The increased risk of ischaemic stroke associated with AF was attenuated by atherosclerotic factors. Our study supports the current view that enhanced control of modifiable cardiovascular risk factors in patients with AF is essential.

scholarly journals Do Salamanders Limit the Abundance of Groundwater Invertebrates in Subterranean Habitats?

Diversity ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 161
Author(s):  
Raoul Manenti ◽  
Enrico Lunghi ◽  
Benedetta Barzaghi ◽  
Andrea Melotto ◽  
Mattia Falaschi ◽  
...  
Keyword(s):  
Mixed Models ◽  
Generalized Linear Mixed Models ◽  
Linear Mixed Models ◽  
Top Down ◽  
Environmental Features ◽  
Fire Salamander ◽  
Negative Effect ◽  
Subterranean Stream ◽  
The Relationship ◽  
Salamander Larvae

Several species of surface salamanders exploit underground environments; in Europe, one of the most common is the fire salamander (Salamandra salamandra). In this study, we investigated if fire salamander larvae occurring in groundwater habitats can affect the abundance of some cave-adapted species. We analyzed the data of abundance of three target taxa (genera Niphargus (Amphipoda; Niphargidae), Monolistra (Isopoda; Sphaeromatidae) and Dendrocoelum (Tricladida; Dedrocoelidae)) collected in 386 surveys performed on 117 sites (pools and distinct subterranean stream sectors), within 17 natural and 24 artificial subterranean habitats, between 2012 and 2019. Generalized linear mixed models were used to assess the relationship between target taxa abundance, fire salamander larvae occurrence, and environmental features. The presence of salamander larvae negatively affected the abundance of all the target taxa. Monolistra abundance was positively related with the distance from the cave entrance of the sites and by their surface. Our study revealed that surface salamanders may have a negative effect on the abundance of cave-adapted animals, and highlited the importance of further investigations on the diet and on the top-down effects of salamanders on the subterranean communities.

A Mixed Approach to the Work-Motherhood Relation: An Application of Fuzzy Set Qualitative Comparative Analysis and Generalized Linear Models

2013 ◽  
Vol 12 (1) ◽  
pp. 31-65 ◽  
Author(s):  
Giulia Maria Dotti Sani ◽  
Mario Quaranta
Keyword(s):  
Comparative Analysis ◽  
Generalized Linear Models ◽  
Fuzzy Set ◽  
Linear Models ◽  
Qualitative Comparative Analysis ◽  
Close Link ◽  
Institutional Contexts ◽  
Complementary Techniques ◽  
Mixed Approach ◽  
The Relationship

Abstract Female labor force participation and total fertility rates have been negatively correlated until the early ’80s. By the end of that decade, however, the relationship changed sign. Scholars have suggested a close link between individual reproductive behavior, labor market participation and institutional contexts, but we still lack clear evidence of the underlying micro-level mechanism. We propose the use of complementary techniques, fuzzy set Qualitative Comparative Analysis and Generalized Linear Models, as the different assumptions underlying the two, combinatory vs. additive, may lead to new insights on how the combination of institutional features can produce different outcomes in terms of the work-motherhood relationship.

Sign in / Sign up

Export Citation Format

Share Document