Academic literature on the topic 'Pseudo-R2'
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Journal articles on the topic "Pseudo-R2"
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Hemmert, Giselmar A. J., Laura M. Schons, Jan Wieseke, and Heiko Schimmelpfennig. "Log-likelihood-based Pseudo-R2 in Logistic Regression." Sociological Methods & Research 47, no. 3 (2016): 507–31. http://dx.doi.org/10.1177/0049124116638107.
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Veall, Michael, and Klaus Zimmermann. "Pseudo-R2's in the ordinal probit model." Journal of Mathematical Sociology 16, no. 4 (1992): 333–42. http://dx.doi.org/10.1080/0022250x.1992.9990094.
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Veall, Michael R., and Klaus F. Zimmermann. "Evaluating Pseudo-R2's for binary probit models." Quality & Quantity 28, no. 2 (1994): 151–64. http://dx.doi.org/10.1007/bf01102759.
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Kataoka, Hiroshi, Mamiko Ohara, Toshio Mochizuki, et al. "Sex Differences in Time-Series Changes in Pseudo-R2 Values Regarding Hyperuricemia in Relation to the Kidney Prognosis." Journal of Personalized Medicine 10, no. 4 (2020): 248. http://dx.doi.org/10.3390/jpm10040248.
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Studies on sex differences in time-series changes in pseudo-R2 values regarding hyperuricemia (HU) in relation to the kidney prognosis among patients with chronic kidney disease (CKD) are scant. The kidney prognosis was evaluated in 200 patients with CKD (median follow-up, 12.3 years). Survival analyses and logistic regression analyses were conducted, generating time-series pseudo-R2 values. We used four definitions of HU according to serum uric acid (SUA) levels (HU6, SUA ≥ 6.0 mg/dL; HU7, SUA ≥ 7.0 mg/dL; HU8, SUA ≥ 8.0 mg/dL) and antihyperuricemic agent use to calculate the mean and percentage of the change in pseudo-R2 values from the 6th year until the end of the study (6Y–End Mean and 6Y–End Change, respectively). The multivariable Cox regression analysis showed that HU7 was significantly associated with kidney outcomes. When stratified by sex, the 6Y–End Mean was clearly higher in women than in men for all HU definitions, with the highest value (0.1755) obtained for HU7 in women. The pseudo-R2 values for HU6 in women showed an increasing pattern, with a 6Y–End Change of 11.4%/year. Thus, it may be clinically meaningful to consider sex differences in the time-series pseudo-R2 values regarding HU and kidney outcomes.
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Grimm, Shawna, Tiffani Dawn Shelton, Charles David Goldman, and Jan Franko. "Prognostic value of preoperative surgical morbidity risk-stratification using morphometric data obtained from routine abdominal CT scans in the setting of pancreatic cancer resection." Journal of Clinical Oncology 31, no. 15_suppl (2013): e17599-e17599. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.e17599.
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e17599 Background: Patient frailty is imparative to surgical planning, post-operative morbidity and mortality, and ultimately the ability to undergo adjuvant therapy in cancer treatment. Sarcopenia has been correlated with long term survival in the setting of pancreatic resection for cancer. However, it has not been evaluated in the early post-operative setting. Here, we evaluate the prognostic value of morphometric parameters measured on abdominal CT scans in fifty patients undergoing pancreatic resections and comparing with postoperative complications. Methods: Post-operative complications of fifty patients who underwent pancreatic resection for suspected neoplasm were graded via Clavien Dindo classification and then correlated with standardized morphometric measurements from CT scans. Results: Thirty-two men and 18 women (age 63±13 years) underwent pancreatic resection for cancer. Total psoas muscle area (2555±791 vs 1821±805,p=0.008), L4-alba distance (113±29 vs 119±27,p=0.597), rectus muscle (10.1±2.5 vs 7.8±4.5,p=0.016) and SQ fat thickness (20±11 vs 29±10,p=0.024). Logistic regression modeling including age, gender, and total psoas area predicted complication occurance (pseudo R2=0.350, p=0.008) and their number (pseudo R2=0.191,p=0.002), but not grade 3 and higher complications (pseudo R2=0.68,p=0.451) or pancreatic leak (pseudo R2=0.020,p=0.873). Similar results were obtained when age and gender variables were combined with rectus muscle thickness (pseudo R2=0.422), L4-alba distance (pseudo R2=0.377), and SQ fat thickness (pseudo R2=0.392). In each case, > Grade 3 complications and pancreatic leak was not predicted with morphometric data, age and gender. Conclusions: There are significant age and gender-related differences in morphometric data obtained from abdominal CT scans. Prognostic models provide statistically significant prediction of complication occurrence, but explain only up to 42% of variability in complication occurrence. Moreover, clinically important complications (grade 3 and higher) and pancreatic leak was not predicted with this model based on our limited dataset.
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Spiess, Martin. "Evaluation of a pseudo-R2 measure for panel probit models." British Journal of Mathematical and Statistical Psychology 54, no. 2 (2001): 325–33. http://dx.doi.org/10.1348/000711001159591.
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Anang, Michael Akrofi, Ruphino Zugle, and Baah Sefa-Ntiri. "Assessing the Adsorptive and Photodegradative Efficiencies of ZSM-11 Synthesized from Rice Husk Ash." Journal of Chemistry 2020 (September 9, 2020): 1–13. http://dx.doi.org/10.1155/2020/6094126.
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Rice husk was used to synthesize zeolite (ZSM-11). FTIR and X-ray diffraction methods were used to characterize the product. The synthesized zeolite was used to treat underground water from some communities in Cape Coast considering parameters such as total dissolved solids, total hardness, conductivity, nitrate, and phosphate. The percentage reduction in PO43− was 96.1% in Ebubonko and 92.5% in Apewosika. Similarly, the NO3− levels also decreased significantly in Kwaprow. The adsorption capability was also determined by using it to remove Pb2+ and Zn2+ from laboratory prepared solutions with varying masses. The percentage reduction recorded 90.57% and 86.61% for the 1.0 g whilst the 1.5 g showed 93.26% and 89.36%, respectively. It was also realized that the adsorption process followed a pseudo-first-order rather than the pseudo-second-order process with their R2 values of 0.9929 and 0.8503 for the pseudo-first-order and 0.9662 and 0.6912 for the second-order for Pb2+ and Zn2+, respectively. The adsorption capacity also favored the Freundlich isotherm with R2 values of 0.7578 and 0.642 rather than Langmuir isotherm with R2 values of 0.1742 and 0.3856 for Pb2+ and Zn2+, respectively. The photodegradation ability of the synthesized zeolite was analyzed using rhodamine blue (RhB) and methyl orange (MO). The process was realized to favor the pseudo-second-order with R2 values of 0.9986 and 0.0007 and a constant K2 of 0.035 and 0.021 for RhB and MO, respectively, whereas the pseudo-first-order showed an R2 value of 0.9376 and 0.9757 with K1 values of 0.03 and 0.02.
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Wang, Guo-Hua, and Jianxin Wu. "Repetitive Reprediction Deep Decipher for Semi-Supervised Learning." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 6170–77. http://dx.doi.org/10.1609/aaai.v34i04.6082.
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Most recent semi-supervised deep learning (deep SSL) methods used a similar paradigm: use network predictions to update pseudo-labels and use pseudo-labels to update network parameters iteratively. However, they lack theoretical support and cannot explain why predictions are good candidates for pseudo-labels. In this paper, we propose a principled end-to-end framework named deep decipher (D2) for SSL. Within the D2 framework, we prove that pseudo-labels are related to network predictions by an exponential link function, which gives a theoretical support for using predictions as pseudo-labels. Furthermore, we demonstrate that updating pseudo-labels by network predictions will make them uncertain. To mitigate this problem, we propose a training strategy called repetitive reprediction (R2). Finally, the proposed R2-D2 method is tested on the large-scale ImageNet dataset and outperforms state-of-the-art methods by 5 percentage points.
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Laitila, Thomas. "A pseudo-R2 measure for limited and qualitative dependent variable models." Journal of Econometrics 56, no. 3 (1993): 341–55. http://dx.doi.org/10.1016/0304-4076(93)90125-o.
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Moacă, Elena-Alina, Ciprian-Valentin Mihali, Ioana-Gabriela Macaşoi, et al. "Fe3O4@C Matrix with Tailorable Adsorption Capacities for Paracetamol and Acetylsalicylic Acid: Synthesis, Characterization, and Kinetic Modeling." Molecules 24, no. 9 (2019): 1727. http://dx.doi.org/10.3390/molecules24091727.
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In this study Fe3O4@C matrix was obtained by combustion method and used hereafter as adsorbent for paracetamol and acetylsalicylic acid removal from aqueous solutions. The Fe3O4@C matrix was characterized by electronic microscopy, X-ray diffraction, thermal analysis, Fourier-transform infrared spectroscopy, and magnetic measurements. Two kinetic models of pseudo first-order and pseudo-second-order for both paracetamol and acetylsalicylic acid were studied. The experimental data were investigated by Langmuir, Freundlich, and Redlich–Peterson adsorption isotherm models. The adsorption followed the Redlich–Peterson and pseudo-second-order models with correlation coefficients R2 = 0.98593 and R2 = 0.99996, respectively, for the adsorption of paracetamol; for the acetylsalicylic acid, the adsorption followed the Freundlich and pseudo-second-order model, with correlation coefficients R2 = 0.99421 and R2 = 0.99977, respectively. The equilibrium was quickly reached after approximately 1h for the paracetamol adsorption and approximately 2h for acetylsalicylic acid adsorption. According to the Langmuir isotherm, the maximum adsorption capacity of the magnetic matrix was 142.01 mg·g−1 for the retention of paracetamol and 234.01 mg·g−1 for the retention of acetylsalicylic acid. The benefits of using the Fe3O4@C matrix are the low cost of synthesis and its easy and fast separation from solution by using an NdBFe magnet.
Dissertations / Theses on the topic "Pseudo-R2"
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Rouam, Sigrid Laure. "Développement d’un indice de séparabilité adapté aux données de génomique en analyse de survie." Thesis, Paris 11, 2011. http://www.theses.fr/2011PA11T006/document.
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Dans le domaine de l’oncogénomique, l’un des axes actuels de recherche est l’identification de nouveaux marqueurs génétiques permettant entre autres de construire des règles prédictives visant à classer les patients selon le risque d’apparition d’un événement d’intérêt (décès ou récidive tumorale). En présence de telles données de haute dimension, une première étape de sélection parmi l’ensemble des variables candidates est généralement employée afin d’identifier les marqueurs ayant un intérêt explicatif jugé suffisant. Une question récurrente pour les biologistes est le choix de la règle de sélection. Dans le cadre de l’analyse de survie, les approches classiques consistent à ranger les marqueurs génétiques à partir du risque relatif ou de quantités issues de test statistiques (p-value, q-value). Cependant, ces méthodes ne sont pas adaptées à la combinaison de résultats provenant d’études hétérogènes dont les tailles d’échantillons sont très différentes.Utiliser un indice tenant compte à la fois de l’importance de l’effet pronostique et ne dépendant que faiblement de la taille de l’échantillon permet de répondre à cette problématique. Dans ce travail, nous proposons un nouvel indice de capacité de prédiction afin de sélectionner des marqueurs génomiques ayant un impact pronostique sur le délai de survenue d’un évènement.Cet indice étend la notion de pseudo-R2 dans le cadre de l’analyse de survie. Il présente également une interprétation originale et intuitive en terme de « séparabilité ». L’indice est tout d’abord construit dans le cadre du modèle de Cox, puis il est étendu à d’autres modèles plus complexes à risques non-proportionnels. Des simulations montrent que l’indice est peu affectée par la taille de l’échantillon et la censure. Il présente de plus une meilleure séparabilité que les indices classiques de la littérature. L’intérêt de l’indice est illustré sur deux exemples. Le premier consiste à identifier des marqueurs génomiques communs à différents types de cancers. Le deuxième, dans le cadre d’une étude sur le cancer broncho-pulmonaire, montre l’intérêt de l’indice pour sélectionner des facteurs génomiques entraînant un croisement des fonctions de risques instantanés pouvant être expliqué par un effet « modulateur » entre les marqueurs. En conclusion, l’indice proposé est un outil prometteur pouvant aider les chercheurs à identifier des listes de gènes méritant des études plus approfondies<br>In oncogenomics research, one of the main objectives is to identify new genomic markers so as to construct predictive rules in order to classify patients according to time-to-event outcomes (death or tumor relapse). Most of the studies dealing with such high throughput data usually rely on a selection process in order to identify, among the candidates, the markers having a prognostic impact. A common problem among biologists is the choice of the selection rule. In survival analysis, classical procedures consist in ranking genetic markers according to either the estimated hazards ratio or quantities derived from a test statistic (p-value, q-value). However, these methods are not suitable for gene selection across multiple genomic datasets with different sample sizes.Using an index taking into account the magnitude of the prognostic impact of factors without being highly dependent on the sample size allows to address this issue. In this work, we propose a novel index of predictive ability for selecting genomic markers having a potential impact on timeto-event outcomes. This index extends the notion of "pseudo-R2" in the ramework of survival analysis. It possesses an original and straightforward interpretation in terms of "separability". The index is first derived in the framework of the Cox model and then extended to more complex non-proportional hazards models. Simulations show that our index is not substantially affected by the sample size of the study and the censoring. They also show that its separability performance is higher than indices from the literature. The interest of the index is illustrated in two examples. The first one aims at identifying genomic markers with common effects across different cancertypes. The second shows, in the framework of a lung cancer study, the interest of the index for selecting genomic factor with crossing hazards functions, which could be explained by some "modulating" effects between markers. The proposed index is a promising tool, which can help researchers to select a list of features of interest for further biological investigations
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Rouam, Sigrid Laure. "Développement d'un indice de séparabilité adapté aux données de génomique en analyse de survie." Phd thesis, Université Paris Sud - Paris XI, 2011. http://tel.archives-ouvertes.fr/tel-00718743.
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Dans le domaine de l'oncogénomique, l'un des axes actuels de recherche est l'identification de nouveaux marqueurs génétiques permettant entre autres de construire des règles prédictives visant à classer les patients selon le risque d'apparition d'un événement d'intérêt (décès ou récidive tumorale). En présence de telles données de haute dimension, une première étape de sélection parmi l'ensemble des variables candidates est généralement employée afin d'identifier les marqueurs ayant un intérêt explicatif jugé suffisant. Une question récurrente pour les biologistes est le choix de la règle de sélection. Dans le cadre de l'analyse de survie, les approches classiques consistent à ranger les marqueurs génétiques à partir du risque relatif ou de quantités issues de test statistiques (p-value, q-value). Cependant, ces méthodes ne sont pas adaptées à la combinaison de résultats provenant d'études hétérogènes dont les tailles d'échantillons sont très différentes.Utiliser un indice tenant compte à la fois de l'importance de l'effet pronostique et ne dépendant que faiblement de la taille de l'échantillon permet de répondre à cette problématique. Dansce travail, nous proposons un nouvel indice de capacité de prédiction afin de sélectionner des marqueurs génomiques ayant un impact pronostique sur le délai de survenue d'un évènement.Cet indice étend la notion de pseudo-R2 dans le cadre de l'analyse de survie. Il présente également une interprétation originale et intuitive en terme de " séparabilité ". L'indice est tout d'abord construit dans le cadre du modèle de Cox, puis il est étendu à d'autres modèles plus complexes à risques non-proportionnels. Des simulations montrent que l'indice est peu affectée par la taille de l'échantillon et la censure. Il présente de plus une meilleure séparabilité que les indices classiques de la littérature. L'intérêt de l'indice est illustré sur deux exemples. Le premier consiste à identifier des marqueurs génomiques communs à différents types de cancers. Le deuxième, dans le cadre d'une étude sur le cancer broncho-pulmonaire, montre l'intérêt de l'indice pour sélectionner des facteurs génomiques entraînant un croisement des fonctions de risques instantanés pouvant être expliqué par un effet " modulateur " entre les marqueurs. En conclusion, l'indice proposé est un outil prometteur pouvant aider les chercheurs à identifier des listes de gènes méritant des études plus approfondies.
Book chapters on the topic "Pseudo-R2"
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Defo, Celestin, and Ravinder Kaur. "Kinetics of Heavy Metals Adsorption on Gravels Derived From Subsurface Flow Constructed Wetland." In Advances in Environmental Engineering and Green Technologies. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1871-7.ch011.
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Adsorption kinetics of Ni, Cr, and Pb on gravels collected from constructed wetland was studied at varied metal concentrations and contact period for estimating the removal of heavy metals from wastewater. Batch experiments were conducted by shaking 120 ml of metal solutions having 5 concentration levels each of Ni (1.0, 2.0, 3.5, 5.0 and 6.0 mg l-1), Cr (1.0, 2.0, 3.0, 4.5 and 6.0 mg l-1), and Pb (1.0, 3.0, 6.0, 8.0 and 12.0 mg l-1) with 50 g of gravels for as function of time. Adsorption of Ni, Cr, and Pb on gravels ranged from 34.8 to 47.2, 42.7-54.9, and 47.5-56.9%, indicating their removal in the order: Pb &gt; Cr &gt; Ni. Freundlich model showed a good fit for Ni and Cr (R2&gt;0.9) while Langmuir model fitted better for Pb (R2= 0.7). The pseudo-second-order model showed the best fit to simulate the adsorption rates of these metals on gravel.
Conference papers on the topic "Pseudo-R2"
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Seniūnaitė, Jurgita, Rasa Vaiškūnaitė, and Kristina Bazienė. "Mathematical Modelling for Copper and Lead Adsorption on Coffee Grounds." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.007.
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Research studies on the adsorption kinetics are conducted in order to determine the absorption time of heavy metals on coffee grounds from liquid. The models of adsorption kinetics and adsorption diffusion are based on mathe-matical models (Cho et al. 2005). The adsorption kinetics can provide information on the mechanisms occurring be-tween adsorbates and adsorbents and give an understanding of the adsorption process. In the mathematical modelling of processes, Lagergren’s pseudo-first- and pseudo-second-order kinetics and the intra-particle diffusion models are usually applied. The mathematical modelling has shown that the kinetics of the adsorption process of heavy metals (copper (Cu) and lead (Pb)) is more appropriately described by the Lagergren’s pseudo-second-order kinetic model. The kinetic constants (k2Cu = 0.117; k2Pb = 0,037 min−1) and the sorption process speed (k2qeCu = 0.0058–0.4975; k2qePb = 0.021–0.1661 mg/g per min) were calculated. After completing the mathematical modelling it was calculated that the Langmuir isotherm better reflects the sorption processes of copper (Cu) (R2 = 0.950), whilst the Freundlich isotherm – the sorption processes of lead (Pb) (R2 = 0.925). The difference between the mathematically modelled and experimen-tally obtained sorption capacities for removal of heavy metals on coffee grounds from aqueous solutions is 0.059–0.164 mg/l for copper and 0.004–0.285 mg/l for lead. Residual concentrations of metals in a solution showed difference of 1.01 and 0.96 mg/l, respectively.
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Cajucom, Ernesto Jr S., and Lolibeth V. Figueroa. "SURFACE MODIFICATION OF CANARIUM OVATUMENGL.(PILI) SHELL AS ADSORBENT OF LEAD(Pb2+) FROM AQUEOUS SOLUTION." In International Trends in Science and Technology. RS Global Sp. z O.O., 2021. http://dx.doi.org/10.31435/rsglobal_conf/30032021/7476.
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This study was carried out to investigate the efficiency of raw pili shell (RPS) and the surface modified pili shell using EDTA (EMPS) and oxalic acid (OMPS). A comparative study on the adsorption capacity of the adsorbents was performed against lead (Pb2+) from aqueous solution. The adsorbents were characterized by FTIR, which showed higher peak of adsorption bands of carboxylic groups on the acid modified pili shells. Scanning electron microscope orSEM was also used to describe the surface morphology of the adsorbents. The linear form of Langmuir and Freundlich models were applied to represent adsorption data. The calculated equilibrium data of Pb (II) best fitted to Langmuir compare to Freundlich isotherm model with maximum adsorption capacity (qmax) of 27.03 mg/g and 45.45 mg/g using EMPS and OMPS, respectively. Kinetic sorption models were used to determine the adsorption mechanism and the kinetic data of all the adsorbents correlated (R2=1) wellwith the pseudo second order kinetic model. Among the three adsorbents, OMPS shown higher percent removal of lead compared to RPS and EMPS. The large adsorption capacity rate indicated that chemically modified pili shell in present study has great potential to be used as a cost-effective adsorbent for the removal of lead ions from the water.