Inequality of opportunity in the double burden of malnutrition in Mexico.

This paper proposes a pseudo-birth-cohort approach to deal with a lack of longitudinal data to measure health inequities over time. Using Roemer's framework for inequality of opportunity, this study measures ex-ante and ex-post inequalities in malnutrition, a concept that spans both sides of the nutrition continuum. The total contribution of observed circumstances and the direct contribution of observed efforts to the variation of malnutrition are disentangled for people born between 1983 and 1988 in Mexico. Results indicate that inequality of opportunity has been persistent across this 30-year lifespan for that cohort. Some evidence suggests that a lack of opportunities has been transmitted from parents to children and that people's circumstances account for most of the explained variation in the double burden of malnutrition. However, stratifying the analysis by sex shows that efforts account for more of the explained variation of inequality of opportunity for women in their middle adulthood than for men in most of the outcomes analyzed.

Incremental Healthcare Costs of Diabetes Mellitus in a Middle-Income Country Using Administrative Healthcare Data.

OBJECTIVES: To estimate the incremental medical cost of diabetes mellitus using information from administrative databases in Colombia. METHODS: We carried out a retrospective cohort study with administrative health databases from Colombian population affiliated in the contributory health insurance scheme. We used an operative definition to select the cohort with diabetes. Incremental cost and cost ratio of diabetes were estimated using an inverse probability weighting of treatment approach to find the causal effect of having the disease. Weights were calculated by a propensity score method using a Random Forest model. The flexibility of this machine learning algorithm allows to have a better specification and bias reduction. Additionally, we reported incremental costs and cost ratios with confidence intervals using bootstrapping and analyzed costs by age groups and complications associated with diabetes. RESULTS: The estimated prevalence of diabetes was 2834 per 100 000 cases, in 2018. The group with diabetes was comprised 634 015 people and the control group 1 524 808. The calculated annual direct medical cost was $860, for which the incremental cost was $493 and the cost ratio 2.34. The incremental annual cost for some type of complication ranges from $1239 to $2043, renal complication being the most expensive. Incremental cost by age groups ranges from $347 to $878, being higher in younger people. CONCLUSIONS: Although the cost of diabetes in Colombia ranges among the global averages and is similar to other Latin-American countries, a greater incremental cost was found in patients with renal, circulatory, and neurologic complications.

The Use of Information Entropy and Expert Opinion in Maximizing the Discriminating Power of Composite Indicators.

This research offers a solution to a highly recognized and controversial problem within the composite indicator literature: sub-indicators weighting. The research proposes a novel hybrid weighting method that maximizes the discriminating power of the composite indicator with objectively defined weights. It considers the experts' uncertainty concerning the conceptual importance of sub-indicators in the multidimensional phenomenon, setting maximum and minimum weights (constraints) in the optimization function. The hybrid weighting scheme, known as the SAW-Max-Entropy method, avoids attributing weights that are incompatible with the multidimensional phenomenon's theoretical framework. At the same time, it reduces the influence of assessment errors and judgment biases on composite indicator scores. The research results show that the SAW-Max-Entropy weighting scheme achieves greater discriminating power than weighting schemes based on the Entropy Index, Expert Opinion, and Equal Weights. The SAW-Max-Entropy method has high application potential due to the increasing use of composite indicators across diverse areas of knowledge. Additionally, the method represents a robust response to the challenge of constructing composite indicators with superior discriminating power.

A goal-based weighting for composite indicators constructed through Ordered Weighted Averaging (OWA) operator.

The Ordered Weighted Averaging (OWA) operator is a multicriteria method that has conquered space among researchers in the composite indicators field. Typically, OWA operator weights are defined by the decision maker. This type of weighting is highly criticized, as decision-makers are susceptible to errors and bias in judgment. Some methods have been used to define OWA operator weights objectively. However, none of them is concerned about the quality of the composite indicator. This paper introduces a method that defines the weights of the OWA operator based on two quality parameters of the composite indicator: the ability to capture the concept of the multidimensional phenomenon and the informational loss. The method can be implemented in Microsoft Excel Solver and has a high degree of flexibility and applicability in problems of a multidimensional nature and a high degree of appropriation by researchers and practitioners in the area.•Defines weights that maximize the ability of the composite indicator to capture the concept of the multidimensional phenomenon.•Considers restrictions to limit the informational loss of the composite indicator or emphasize positive or negative aspects of the multidimensional phenomenon.•Offers flexibility in setting the objective and constraints of the optimization algorithm.

Outcomes of preoperative chemotherapy for colorectal cancer with peritoneal metastasis underwent cytoreductive surgery.

BACKGROUND: This study aims to assess and compare the extent to which preoperative chemotherapy prior to CRS improves survival in patients diagnosed with CRCPM. METHODS: We included 251 patients from 2012 to 2019 in our center. Inverse probability of treatment weighting (IPTW) analysis was used to minimize the selection bias. Survival analysis was performed to compare the survival outcomes. Multivariate Cox regression analysis was conducted to identify prognostic factors. RESULT: The baseline characteristics were well balanced using IPTW (standardized mean difference < 0.1). Preoperative chemotherapy cannot significantly improve overall survival (HR, 1.03; 95% CI 0.71-1.49; P = 0.88). In subgroup analysis, we found that intestinal obstruction after preoperative chemotherapy significantly reduced survival (HR, 2.25; 95% CI 1.01-5.03; P = 0.048), while in the upfront surgery group, intestinal obstruction had no impact on prognosis. CONCLUSION: For CRCPM patients treated with CRS, preoperative chemotherapy does not seem to prolong overall survival. Furthermore, the emergence of intestinal obstruction after chemotherapy may compromise the effectiveness of treatment, resulting in a worse prognosis. This finding has important clinical implications for treatment decisions.

Systematic screening strategy for fungal laccase activity of endophytes from Otoba gracilipes with bioremediation potential.

Fungal laccases are promising for biotechnological applications, including bioremediation and dye biotransformation, due to their high redox potential and broad substrate specificity. However, current bioprospecting methods for identifying laccase-producing fungi can be challenging and time-consuming. For early detection, it was developed a three-step, multi-criteria weighting system that evaluates fungal strains based on: First, the biotransformation capacity of three dyes (i.e., Congo red, brilliant blue G-250, and malachite green), at three different pH values, and with a relative weighting supported for the redox potential of each colorant. The relative decolorization coefficient (RDC), used as th2e first classification criterion, expressed their potential performance. Second, under the same conditions, laccase activity was estimated by observing the different degrees of oxidation of a given substrate. The selection criterion was the relative oxidation coefficient (ROC). Finally, laccase activity was quantified in submerged fermentations using three inducers (i.e., loofah sponge, Tween 80, and veratyl alcohol). This multicriteria screening strategy evaluated sixteen isolated endophytic fungal strains from Otoba gracilipes. The system identified Beltraniopsis sp. ET-17 (at pH values of 5.00 and 5.50) as a promising strain for dye biotransformation, and Phlebia floridensis as the best laccase producer, achieving a high activity of 116 µmol min-1 L-1 with loofah sponge as an inducer. In-vitro testing confirmed the efficacy of P. floridensis, with 53.61 % decolorization of a dye mixture (brilliant blue-Congo red. ratio 1:1) after 15 days of incubation. Thus, with the proposed screening strategy it was possible to highlight two species of interest at an early bioprospecting stage on a Colombian native tree poorly explored.

Association between prolonged corticosteroids use in COVID-19 and increased mortality in hospitalized patients: a retrospective study with inverse probability of treatment weighting analysis.

BACKGROUND: Previous studies have demonstrated a beneficial effect of early use of corticosteroids in patients with COVID-19. This study aimed to compare hospitalized patients with COVID-19 who received short-course corticosteroid treatment with those who received prolonged-course corticosteroid treatment to determine whether prolonged use of corticosteroids improves clinical outcomes, including mortality. METHODS: This is a retrospective cohort study including adult patients with positive testing for Sars-CoV-2 hospitalized for more than 10 days. Data were obtained from electronic medical records. Patients were divided into two groups, according to the duration of treatment with corticosteroids: a short-course (10 days) and a prolonged-course (longer than 10 days) group. Inverse probability treatment weighting (IPTW) analysis was used to evaluate whether prolonged use of corticosteroids improved outcomes. The primary outcome was in-hospital mortality. Secondary outcomes were hospital infection and the association of different doses of corticosteroids with hospital mortality. Restricted cubic splines were used to assess the nonlinear association between mortality and dose and duration of corticosteroids use. RESULTS: We enrolled 1,539 patients with COVID-19. Among them, 1127 received corticosteroids for more than 10 days (prolonged-course group). The in-hospital mortality was higher in patients that received prolonged course corticosteroids (39.5% vs. 26%, p < 0.001). The IPTW revealed that prolonged use of corticosteroids significantly increased mortality [relative risk (RR) = 1.52, 95% confidence interval (95% CI): 1.24-1.89]. In comparison to short course treatment, the cubic spline analysis showed an inverted U-shaped curve for mortality, with the highest risk associated with the prolonged use at 30 days (RR = 1.50, 95% CI 1.21-1.78). CONCLUSIONS: Prolonged course of treatment with corticosteroids in hospitalized patients with COVID-19 was associated with higher mortality.

La hermenéutica constitucional y la cultura de derechos humanos en tiempos de pandemia COVID-19 / The Constitutional hermeneutics and the human rights culture in epoch of the covid-19 pandemic / A hermenêutica constitucional e a cultura dos direitos humanos em tempos de pandemia COVID-19

RESUMEN La crisis del COVID-19, sus implicaciones socio jurídicas, se abordan mediante su incidencia en los derechos humanos, consecuencia del Estado de emergencia dictado en Colombia en el año 2020, para el resguardo del derecho a la salud, pero generando a su vez una situación de conflictos entre diversos tipos de derechos. El trabajo constituye una reflexión sustentada en una investigación bibliográfica mediante la indagación documental sobre decisiones del poder ejecutivo y de la corte constitucional que ejercen su control, referentes a la regulación jurídica de la pandemia del COVID-19 en Colombia, además de la normativa constitucional y legal y la doctrina referida a la temática. El objetivo es demostrar como la hermenéutica constitucional, mediante los principios de proporcionalidad, ponderación y el contenido esencial, es capaz de fomentar una mayor cultura de los derechos humanos, debido a que estos lineamientos interpretativos pueden ser comprendidos por la ciudadanía mediante una labor que abarque la educación, con el concurso no solo de abogados sino también de maestros, sociólogos, ONG, entre otros.

ABSTRACT The COVID-19 crisis, its socio-legal implications, are addressed through its impact on human rights, as a consequence of the State of Emergency issued in Colombia in 2020, to protect the right to health, but generating in turn a situation of conflicts between different types of rights. The work constitutes a reflection based on a bibliographical investigation through documentary research on decisions of the executive power and the constitutional court that exercise their control, referring to the legal regulation of the COVID-19 pandemic in Colombia, in addition to the constitutional regulations and legal and the doctrine referred to the subject. The objective is to demonstrate how constitutional hermeneutics, through the principles of proportionality, weighting and essential content, is capable of promoting a greater culture of human rights, because these interpretative guidelines can be understood by citizens through work that encompasses education, with the participation not only of lawyers but also of teachers, sociologists, NGO, among others.

RESUMО A crise da COVID-19 e suas implicações sócio-legais são abordadas através de seu impacto nos direitos humanos, conseqüência do Estado de Emergência ditado na Colômbia no ano 2020, para salvaguardar o direito à saúde, mas ao mesmo tempo gerando uma situação de conflito entre diferentes tipos de direitos. O trabalho constitui uma reflexão baseada em uma pesquisa bibliográfica através de pesquisa documental sobre decisões do poder executivo e do tribunal constitucional que exercem seu controle, referindo-se à regulamentação legal da pandemia da COVID-19 na Colômbia, além da regulamentação constitucional e legal e da doutrina sobre o assunto. O objetivo é demonstrar como a hermenêutica constitucional, através dos princípios de proporcionalidade, ponderação e conteúdo essencial, é capaz de promover uma maior cultura de direitos humanos, visto que estas diretrizes interpretativas podem ser compreendidas pelos cidadãos através da educação, com a ajuda não só de advogados, mas também de professores, sociólogos, ONGs, entre outros.

Influence of Epoxy Resin Curing Kinetics on the Mechanical Properties of Carbon Fiber Composites.

In this study, the kinetic parameters belonging to the cross-linking process of a modified epoxy resin, Aerotuf 275-34™, were investigated. Resin curing kinetics are crucial to understanding the structure-property-processing relationship for manufacturing high-performance carbon-fiber-reinforced polymer composites (CFRPCs). The parameters were obtained using differential scanning calorimetry (DSC) measurements and the Flynn-Wall-Ozawa, Kissinger, Borchardt-Daniels, and Friedman approaches. The DSC thermograms show two exothermic peaks that were deconvoluted as two separate reactions that follow autocatalytic models. Furthermore, the mechanical properties of produced carbon fiber/Aerotuf 275-34™ laminates using thermosetting polymers such as epoxies, phenolics, and cyanate esters were evaluated as a function of the conversion degree, and a close correlation was found between the degree of curing and the ultimate tensile strength (UTS). We found that when the composite material is cured at 160 °C for 15 min, it reaches a conversion degree of 0.97 and a UTS value that accounts for 95% of the maximum value obtained at 200 °C (180 MPa). Thus, the application of such processing conditions could be enough to achieve good mechanical properties of the composite laminates. These results suggest the possibility for the development of strategies towards manufacturing high-performance materials based on the modified epoxy resin (Aerotuf 275-34™) through the curing process.

Gender differences in high-school dropout: Vulnerability and adolescent fertility in Chile.

The original concerns about the consequences of adolescent fertility assumed that pregnancy is a turning point, which altered teens' life trajectories in terms of school progress, human capital accumulation and labor force participation, placing them on a path of vulnerability. However, several years of research have shown that teenagers who become pregnant are not a random sample of the population, but a selective sample, more likely to have limited socioeconomic resources and other characteristics that made them a vulnerable group to begin with. This paper studies the association between adolescent fertility and high school dropout in Chile taking that selectivity in consideration. We analyze the dropout of teen men and women, considering their socioeconomic status, sociodemographic characteristics, and characteristics of their sexual debut. Data comes the VIII Chilean Survey of the Youth, a nationally representative survey of people 15-29 years old applied in 2015. In order to deal with selectivity issues, we use a combination of propensity score weighting techniques and adjusted generalized linear models for estimating the effect of teen parenthood on high school dropout (ATT), for men and women separately. Our best estimates of the effect of teen parenting on the probability of high school dropout is 16-18 percent for women and ten percent for men, which implies that the educational setback of parenthood for women is about twice as high as the setback of men. These findings suggest the need of policies and interventions aimed both to reduce adolescent fertility, but also to facilitate the high school completion of those who already are parents.

Bayesian estimation of the average treatment effect on the treated using inverse weighting.

We develop a Bayesian approach to estimate the average treatment effect on the treated in the presence of confounding. The approach builds on developments proposed by Saarela et al in the context of marginal structural models, using importance sampling weights to adjust for confounding and estimate a causal effect. The Bayesian bootstrap is adopted to approximate posterior distributions of interest and avoid the issue of feedback that arises in Bayesian causal estimation relying on a joint likelihood. We present results from simulation studies to estimate the average treatment effect on the treated, evaluating the impact of sample size and the strength of confounding on estimation. We illustrate our approach using the classic Right Heart Catheterization data set and find a negative causal effect of the exposure on 30-day survival, in accordance with previous analyses of these data. We also apply our approach to the data set of the National Center for Health Statistics Birth Data and obtain a negative effect of maternal smoking during pregnancy on birth weight.

Homoplasy-Based Partitioning Outperforms Alternatives in Bayesian Analysis of Discrete Morphological Data.

Bayesian analysis of morphological data is becoming increasingly popular mainly (but not only) because it allows for time-calibrated phylogenetic inference using relaxed morphological clocks and tip dating whenever fossils are available. As with molecular data, recent studies have shown that modeling among-character rate variation (ACRV) in morphological matrices greatly improves phylogenetic inference. In a likelihood framework this may be accomplished, for instance, by employing a hidden Markov model to assign characters to rate categories drawn from a (discretized) $\Gamma$ distribution and/or by partitioning data sets according to rate heterogeneity and estimating per-partition branch lengths, conditioned on a single topology. While the first approach is available in many phylogenetic analysis software, there is still no clear consensus on how to partition data, except perhaps in the simplest cases (e.g., "by codon" partitioning of coding sequences). Additionally, there is a trade-off between improvement in likelihood scores and the number of free parameters in the analysis, which rises quickly with the number of partitions. This trade-off may be dealt with by employing statistics that penalize overfitting of complex models, such as Akaike or Bayesian information criteria, or the more recently introduced stepping-stone method for marginal likelihood approximation. We applied the latter to three distinct matrices of discrete morphological data and demonstrated that sorting characters by homoplasy scores (obtained from implied weighting parsimony analysis) outperformed other partitioning strategies (anatomically-based and PartitionFinder2). The method was in fact so efficient in segregating characters by rates of evolution that no within-partition ACRV modeling was necessary, while among-partition rate variation was adequately accommodated by rate multipliers. We conclude that partitioning by homoplasy is a powerful and easy-to-implement strategy to address ACRV in complex data sets. We provide some guidelines focusing on morphological matrices, although this approach may be also applicable to molecular data sets.

Dosimetry and Toxicity Studies of the Novel Sulfonamide Derivative of Sulforhodamine 101([18F]SRF101) at a Preclinical Level.

BACKGROUND: The SR101 N-(3-[18F]Fluoropropyl) sulfonamide ([18F]SRF101) is a Sulforhodamine 101 derivative that was previously synthesised by our group. The fluorescent dye SR101 has been reported as a marker of astroglia in the neocortex of rodents in vivo. OBJECTIVE: The aim of this study was to perform a toxicological evaluation of [18F]SRF101 and to estimate human radiation dosimetry based on preclinical studies. METHODS: Radiation dosimetry studies were conducted based on biokinetic data obtained from a mouse model. A single-dose toxicity study was carried out. The toxicological limit chosen was <100 µg, and allometric scaling with a safety factor of 100 for unlabelled SRF101 was selected. RESULTS: The absorbed and effective dose estimated using OLINDA/EXM V2.0 for male and female dosimetric models presented the same tendency. The highest total absorbed dose values were for different sections of the intestines. The mean effective dose was 4.03 x10-3 mSv/MBq and 5.08 x10-3 mSv/MBq for the male and female dosimetric models, respectively, using tissue-weighting factors from ICRP-89. The toxicity study detected no changes in the organ or whole-body weight, food consumption, haematologic or clinical chemistry parameters. Moreover, lesions or abnormalities were not found during the histopathological examination. CONCLUSION: The toxicological evaluation of SRF101 verified the biosafety of the radiotracer for human administration. The dosimetry calculations revealed that the radiation-associated risk of [18F]SRF101 would be of the same order as other 18F radiopharmaceuticals used in clinical applications. These study findings confirm that the novel radiotracer would be safe for use in human PET imaging.

User-Oriented Summaries Using a PSO Based Scoring Optimization Method.

Automatic text summarization tools have a great impact on many fields, such as medicine, law, and scientific research in general. As information overload increases, automatic summaries allow handling the growing volume of documents, usually by assigning weights to the extracted phrases based on their significance in the expected summary. Obtaining the main contents of any given document in less time than it would take to do that manually is still an issue of interest. In this article, a new method is presented that allows automatically generating extractive summaries from documents by adequately weighting sentence scoring features using Particle Swarm Optimization. The key feature of the proposed method is the identification of those features that are closest to the criterion used by the individual when summarizing. The proposed method combines a binary representation and a continuous one, using an original variation of the technique developed by the authors of this paper. Our paper shows that using user labeled information in the training set helps to find better metrics and weights. The empirical results yield an improved accuracy compared to previous methods used in this field.

Geographical Distribution of COPD Prevalence in the Americas.

Surveys estimating chronic obstructive pulmonary disease (COPD) prevalence are unevenly distributed in the Americas, which make it difficult to estimate accurately its geographical distribution. The geographic information system inverse distance weighted (IDW) interpolation technique has proved to be an effective tool in spatial distribution estimation of epidemiological variables, even when real data are few or widely spread. We aimed to represent cartographically the COPD prevalence in the Americas by means of a blue to red scale representation of the prevalence data, where different values are represented as different colours, and a population density filtered IDW interpolation mapping, where areas with a population density <0.1 inhabitants/km2 are hidden. We systematically searched for prevalence rates from population surveys of individuals 40 years and older, and a COPD diagnosis confirmed by spirometry. Interpolation maps were obtained for the whole Americas, even from extensive areas lacking real data. Maps showed high prevalence values in the Southeast and Southwest regions of Canada bordering the United States; in several states of the Great Lakes region, and in the lower Missouri, Ohio and Mississippi basins of the United States; in the coastal regions of south-eastern and southern Brazil; Uruguay, and the Argentine Pampas. In general, most of the remaining American regions showed intermediate values of COPD prevalence. IDW interpolation seems to be a suitable tool to visually display estimates of COPD prevalence, and it may be a valuable help to draw attention about the worrying prevalence of this preventable and treatable disease.

Optimal selection of molecular descriptors for antimicrobial peptides classification: an evolutionary feature weighting approach.

BACKGROUND: Antimicrobial peptides are a promising alternative for combating pathogens resistant to conventional antibiotics. Computer-assisted peptide discovery strategies are necessary to automatically assess a significant amount of data by generating models that efficiently classify what an antimicrobial peptide is, before its evaluation in the wet lab. Model's performance depends on the selection of molecular descriptors for which an efficient and effective approach has recently been proposed. Unfortunately, how to adapt this method to the selection of molecular descriptors for the classification of antimicrobial peptides and the performance it can achieve, have only preliminary been explored. RESULTS: We propose an adaptation of this successful feature selection approach for the weighting of molecular descriptors and assess its performance. The evaluation is conducted on six high-quality benchmark datasets that have previously been used for the empirical evaluation of state-of-art antimicrobial prediction tools in an unbiased manner. The results indicate that our approach substantially reduces the number of required molecular descriptors, improving, at the same time, the performance of classification with respect to using all molecular descriptors. Our models also outperform state-of-art prediction tools for the classification of antimicrobial and antibacterial peptides. CONCLUSIONS: The proposed methodology is an efficient approach for the development of models to classify antimicrobial peptides. Particularly in the generation of models for discrimination against a specific antimicrobial activity, such as antibacterial. One of our future directions is aimed at using the obtained classifier to search for antimicrobial peptides in various transcriptomes.

Solvent-dependent inversion of circular dichroism signal in naproxen: An unusual effect!

The electronic circular dichroism (ECD) spectra of naproxen enantiomers were studied as a function of solvents using experimental (circular dichroism) and theoretical (time-dependent density functional theory) approaches. The (R)- and (S)-naproxen enantiomers presented an unusual inversion in their ECD signals in the presence of ethanol and water when compared with polar aprotic solvents such as acetonitrile. From a practical point of view, these findings deserve great attention because these solvents are widely used for high-performance liquid chromatography analysis in quality control of chiral pharmaceutical drugs. This is particularly relevant to naproxen because the (S)-naproxen has anti-inflammatory properties, whereas (R)-naproxen is hepatotoxic. A time-dependent density functional theory computer simulation was conducted to investigate the signal inversion using the solvation model based on density, a reparameterization of polarized continuum model. Electronic circular dichroism signals of conformers were calculated by computer simulation and their contribution to the combined spectra obtained according to Boltzmann weighting. It was found that the experimentally observed ECD signal inversion can be associated with the minor or major contribution of different conformers of naproxen.

Sampling Weights for Analyses of Couple Data: Example of the Demographic and Health Surveys.

In some surveys, women and men are interviewed separately in selected households, allowing matching of partner information and analyses of couples. Although individual sampling weights exist for men and women, sampling weights specific for couples are rarely derived. We present a method of estimating appropriate weights for couples that extends methods currently used in the Demographic and Health Surveys (DHS) for individual weights. To see how results vary, we analyze 1912 estimates (means; proportions; linear regression; and simple and multinomial logistic regression coefficients, and their standard errors) with couple data in each of 11 DHS surveys in which the couple weight could be derived. We used two measures of bias: absolute percentage difference from the value estimated with the couple weight and ratio of the absolute difference to the standard error using the couple weight. The latter shows greater bias for means and proportions, whereas the former and a combination of both measures show greater bias for regression coefficients. Comparing results using couple weights with published results using women's weights for a logistic regression of couple contraceptive use in Turkey, we found that 6 of 27 coefficients had a bias above 5 %. On the other hand, a simulation of varying response rates (27 simulations) showed that median percentage bias in a logistic regression was less than 3 % for 17 of 18 coefficients. Two proxy couple weights that can be calculated in all DHS surveys perform considerably better than either male or female weights. We recommend that a couple weight be calculated and made available with couple data from such surveys.

Models for the propensity score that contemplate the positivity assumption and their application to missing data and causality.

Generalized linear models are often assumed to fit propensity scores, which are used to compute inverse probability weighted (IPW) estimators. To derive the asymptotic properties of IPW estimators, the propensity score is supposed to be bounded away from zero. This condition is known in the literature as strict positivity (or positivity assumption), and, in practice, when it does not hold, IPW estimators are very unstable and have a large variability. Although strict positivity is often assumed, it is not upheld when some of the covariates are unbounded. In real data sets, a data-generating process that violates the positivity assumption may lead to wrong inference because of the inaccuracy in the estimations. In this work, we attempt to conciliate between the strict positivity condition and the theory of generalized linear models by incorporating an extra parameter, which results in an explicit lower bound for the propensity score. An additional parameter is added to fulfil the overlap assumption in the causal framework.