Covariance between relatives in multibreed populations: additive model

1993 ◽  
Vol 87 (4) ◽  
pp. 423-430 ◽  
Author(s):  
L. L. Lo ◽  
R. L. Fernando ◽  
M. Grossman
Keyword(s):  
Additive Model ◽  
Covariance Between Relatives

Perbandingan Linieritas Dalam Pendeteksian Faktor-Faktor Yang Mempengaruhi Angka Kematian Bayi Di Provinsi Aceh

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Desfira Ahya ◽  
Inas Salsabila ◽  
Miftahuddin
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Linear Model ◽  
Health Workers ◽  
Additive Model ◽  
Infant Mortality Rate ◽  
Mortality Data ◽  
Important Indicator ◽  
Penalized Spline ◽  
Aceh Province

Angka Kematian Bayi/ Infant Mortality Rate (IMR) merupakan indikator penting dalam mengukur keberhasilan pengembangan kesehatan. Nilai IMR juga dapat digunakan untuk mengetahui tingkat kesehatan ibu, kondisi kesehatan lingkungan dan secara umum, tingkat pengembangan sosio-ekonomi masyarakat. Penelitian ini bertujuan untuk memperoleh model IMR terbaik menggunakan tiga pendekatan: Model Linear, Model Linear Tergeneralisir dan Model Aditif Tergeneralisir dengan basis P-spline. Sebagai tambahan, berdasarkan model tersebut akan terlihat variabel yang mempengaruhi tingkat kematian bayi di provinsi Aceh. Penelitian ini menggunakan data jumlah kematian bayi di tahun 2013-2015. Data dalam penelitian ini diperoleh dari Profil Kesehatan Aceh. Hasil menunjukkan bahwa model terbaik dalam menjelaskan angka kematian bayi di provinsi Aceh tahun 2013-2015 ialah Model Linear Tergeneralisir dengan basis P-spline menggunakan parameter penghalusan 100 dan titik knots 8. Faktor yang sangat mempengaruhi angka kematian ialah jumlah pekerja yang sehat.   Infant mortality rate (IMR) is an important indicator in measuring the success of health development. IMR also can be used to knowing the level of maternal health, environmental health conditions and generally the level of socio-economic development in community. This research aims to get the best model of infant mortality data using three approaches: Linear Model, Generalized Linear Model and Generalized Additive Model with Penalized Spline (P-spline) base. In addition, based on the model can be seen the variables that affect to infant mortality in Aceh Province. This research uses data number of infant mortality in Aceh Province period 2013-2015. The data in this research were obtained from Aceh’s Health Profile. The results show that the best model can be explain infant mortality rate in Aceh Province period 2013-2015 is GAM model with P-spline base using smoothing parameter 100 and knots 8. Factor that high effect to infant mortality is number of health workers.

Additive-multiplicative description of extrathermodynamic relations: Application to solvent effect

1990 ◽  
Vol 55 (3) ◽  
pp. 634-643 ◽  
Author(s):  
Oldřich Pytela
Keyword(s):  
Solvent Effect ◽  
Additive Model ◽  
Multiplicative Model ◽  
Data Matrix ◽  
Statistical Parameters ◽  
Model Application ◽  
Mutual Correlation ◽  
Linear Free Energy ◽  
Cross Terms ◽  
Energy Relationships

The paper is focused on evaluation of significance of the additive-multiplicative model of extrathermodynamic relations (linear free energy relationships) as compared with the additive model. Application of the method of conjugated deviations to a data matrix describing manifestations of solvent effects in 367 processes in solutions (6 334 data) has shown that introduction of cross-terms into the additive model is statistically significant for a model with two and particularly three parameters. At the same time the calculation has provided a new set of statistical parameters for description of solvent effect with application of the additive-multiplicative model. Compared with an analogous set designated for the additive model, the new parameters show a lower mutual correlation, retaining the same nature of the properties described, i.e. polarity-acidity (PAC parameter), polarity-basicity (PBC), and polarity-polarizability (PPC).

scholarly journals Predicting Malaria Transmission Dynamics in Dangassa, Mali: A Novel Approach Using Functional Generalized Additive Models

2020 ◽  
Vol 17 (17) ◽  
pp. 6339
Author(s):  
François Freddy Ateba ◽  
Manuel Febrero-Bande ◽  
Issaka Sagara ◽  
Nafomon Sogoba ◽  
Mahamoudou Touré ◽  
...  
Keyword(s):  
Wind Speed ◽  
Malaria Incidence ◽  
Generalized Additive Models ◽  
Community Health Center ◽  
Additive Model ◽  
Additive Models ◽  
Functional Regression ◽  
Novel Approach ◽  
Malaria Incidence Rate ◽  
Mean Wind Speed

Mali aims to reach the pre-elimination stage of malaria by the next decade. This study used functional regression models to predict the incidence of malaria as a function of past meteorological patterns to better prevent and to act proactively against impending malaria outbreaks. All data were collected over a five-year period (2012–2017) from 1400 persons who sought treatment at Dangassa’s community health center. Rainfall, temperature, humidity, and wind speed variables were collected. Functional Generalized Spectral Additive Model (FGSAM), Functional Generalized Linear Model (FGLM), and Functional Generalized Kernel Additive Model (FGKAM) were used to predict malaria incidence as a function of the pattern of meteorological indicators over a continuum of the 18 weeks preceding the week of interest. Their respective outcomes were compared in terms of predictive abilities. The results showed that (1) the highest malaria incidence rate occurred in the village 10 to 12 weeks after we observed a pattern of air humidity levels >65%, combined with two or more consecutive rain episodes and a mean wind speed <1.8 m/s; (2) among the three models, the FGLM obtained the best results in terms of prediction; and (3) FGSAM was shown to be a good compromise between FGLM and FGKAM in terms of flexibility and simplicity. The models showed that some meteorological conditions may provide a basis for detection of future outbreaks of malaria. The models developed in this paper are useful for implementing preventive strategies using past meteorological and past malaria incidence.

scholarly journals Immediate and Delayed Meteorological Effects on COVID-19 Time-Varying Infectiousness in Tropical Cities

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 513
Author(s):  
Xerxes Seposo ◽  
Chris Fook Sheng Ng ◽  
Lina Madaniyazi
Keyword(s):  
Model Fitting ◽  
Additive Model ◽  
The Philippines ◽  
Air Pressure ◽  
Dew Point ◽  
Outcome Variable ◽  
Climatic Data ◽  
Time Varying ◽  
Rt Pcr ◽  
National Climatic Data Center

The novel coronavirus, which was first reported in Wuhan, China in December 2019, has been spreading globally at an unprecedented rate, leading to the virus being declared a global pandemic by the WHO on 12 March 2020. The clinical disease, COVID-19, associated with the pandemic is caused by the pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Aside from the inherent transmission dynamics, environmental factors were found to be associated with COVID-19. However, most of the evidence documenting the association was from temperate locations. In this study, we examined the association between meteorological factors and the time-varying infectiousness of COVID-19 in the Philippines. We obtained the daily time series from 3 April 2020 to 2 September 2020 of COVID-19 confirmed cases from three major cities in the Philippines, namely Manila, Quezon, and Cebu. Same period city-specific daily average temperature (degrees Celsius; °C), dew point (degrees Celsius; °C), relative humidity (percent; %), air pressure (kilopascal; kPa), windspeed (meters per second; m/s) and visibility (kilometer; km) data were obtained from the National Oceanic and Atmospheric Administration—National Climatic Data Center. City-specific COVID-19-related detection and intervention measures such as reverse transcriptase polymerase chain reaction (RT-PCR) testing and community quarantine measures were extracted from online public resources. We estimated the time-varying reproduction number (Rt) using the serial interval information sourced from the literature. The estimated Rt was used as an outcome variable for model fitting via a generalized additive model, while adjusting for relevant covariates. Results indicated that a same-day and the prior week’s air pressure was positively associated with an increase in Rt by 2.59 (95% CI: 1.25 to 3.94) and 2.26 (95% CI: 1.02 to 3.50), respectively. Same-day RT-PCR was associated with an increase in Rt, while the imposition of community quarantine measures resulted in a decrease in Rt. Our findings suggest that air pressure plays a role in the infectiousness of COVID-19. The determination of the association of air pressure on infectiousness, aside from the testing frequency and community quarantine measures, may aide the current health systems in controlling the COVID-19 infectiousness by integrating such information into an early warning platform.

scholarly journals The Struggle of Ash—Insights from Long-Term Survey in Latvia

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 340
Author(s):  
Ilze Matisone ◽  
Roberts Matisons ◽  
Āris Jansons
Keyword(s):  
Local Density ◽  
Additive Model ◽  
Tree Height ◽  
Natural Resistance ◽  
Critical Conditions ◽  
Tree Level ◽  
Future Potential ◽  
Genetic And Environmental Factors ◽  
Long Term Survey

The dieback of common ash (Fraxinus excelsior L.) has dramatically decreased the abundance of the species in Europe; however, tolerance of trees varies regionally. The tolerance of trees is considered to be a result of synergy of genetic and environmental factors, suggesting an uneven future potential of populations. This also implies that wide extrapolations would be biased and local information is needed. Survival of ash during 2005–2020, as well as stand- and tree-level variables affecting them was assessed based on four surveys of 15 permanent sampling plots from an eastern Baltic region (Latvia) using an additive model. Although at the beginning of dieback a relatively low mortality rate was observed, it increased during the 2015–2020 period, which was caused by dying of the most tolerant trees, though single trees have survived. In the studied stands, ash has been gradually replaced by other local tree species, though some recruitment of ash was locally observed, implying formation of mixed broadleaved stands with slight ash admixture. The survival of trees was related to tree height and position within a stand (relative height and local density), though the relationships were nonlinear, indicating presence of critical conditions. Regarding temporal changes, survival rapidly dropped during the first 16 years, stabilizing at a relatively low level. Although low recruitment of ash still implies plummeting economic importance of the species, the observed responses of survival, as well as the recruitment, imply potential to locally improve the survival of ash via management (tending), hopefully providing time for natural resistance to develop.

scholarly journals Household mold exposure interacts with inflammation-related genetic variants on childhood asthma: a case–control study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yu Zhang ◽  
Li Hua ◽  
Quan-Hua Liu ◽  
Shu-Yuan Chu ◽  
Yue-Xin Gan ◽  
...  
Keyword(s):  
Childhood Asthma ◽  
Case Control Study ◽  
Additive Model ◽  
Case Control ◽  
Nucleotide Polymorphisms ◽  
Additive Interaction ◽  
Asthmatic Children ◽  
Gene Environment ◽  
Mold Exposure ◽  
Control Study

Abstract Background A number of studies have examined the association between mold exposure and childhood asthma. However, the conclusions were inconsistent, which might be partly attributable to the lack of consideration of gene function, especially the key genes affecting the pathogenesis of childhood asthma. Research on the interactions between genes and mold exposure on childhood asthma is still very limited. We therefore examined whether there is an interaction between inflammation-related genes and mold exposure on childhood asthma. Methods A case–control study with 645 asthmatic children and 910 non-asthmatic children aged 3–12 years old was conducted. Eight single nucleotide polymorphisms (SNPs) in inflammation-related genes were genotyped using MassARRAY assay. Mold exposure was defined as self-reported visible mold on the walls. Associations between visible mold exposure, SNPs and childhood asthma were evaluated using logistic regression models. In addition, crossover analyses were used to estimate the gene-environment interactions on childhood asthma on an additive scale. Results After excluding children without information on visible mold exposure or SNPs, 608 asthmatic and 839 non-asthmatic children were included in the analyses. Visible mold exposure was reported in 151 asthmatic (24.8%) and 119 non-asthmatic children (14.2%) (aOR 2.19, 95% CI 1.62–2.97). The rs7216389 SNP in gasdermin B gene (GSDMB) increased the risk of childhood asthma with each C to T substitution in a dose-dependent pattern (additive model, aOR 1.32, 95% CI 1.11–1.57). Children carrying the rs7216389 T allele and exposed to visible mold dramatically increased the risk of childhood asthma (aOR 3.21; 95% CI 1.77–5.99). The attributable proportion due to the interaction (AP: 0.47, 95% CI 0.03–0.90) and the relative excess risk due to the interaction (RERI: 1.49, 95% CI 0–2.99) were statistically significant. Conclusions In the present study, there was a significant additive interaction between visible mold exposure and rs7216389 SNP on childhood asthma. Future studies need to consider the gene-environment interactions when exploring the risk factors of childhood asthma.

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